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diff --git a/...umentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api.rst b/...umentation/openvino_legacy_features/mo_ovc_transition/legacy_conversion_api.rst
@@ -8,13 +8,13 @@ Legacy Conversion API
    :maxdepth: 1
    :hidden:
 
-   openvino_docs_MO_DG_prepare_model_convert_model_Converting_Model
-   openvino_docs_MO_DG_prepare_model_convert_model_Cutting_Model
-   openvino_docs_MO_DG_Additional_Optimization_Use_Cases
-   openvino_docs_MO_DG_FP16_Compression
-   openvino_docs_MO_DG_Python_API
-   openvino_docs_MO_DG_prepare_model_Model_Optimizer_FAQ
-   Supported_Model_Formats_MO_DG
+   Setting Input Shapes <openvino_docs_MO_DG_prepare_model_convert_model_Converting_Model>
+   Cutting Off Parts of a Model <openvino_docs_MO_DG_prepare_model_convert_model_Cutting_Model>
+   Embedding Preprocessing Computation <openvino_docs_MO_DG_Additional_Optimization_Use_Cases>
+   Compressing a Model to FP16 <openvino_docs_MO_DG_FP16_Compression>
+   Convert Models Represented as Python Objects <openvino_docs_MO_DG_Python_API>
+   Model Optimizer Frequently Asked Questions <openvino_docs_MO_DG_prepare_model_Model_Optimizer_FAQ>
+   Supported Model Formats <Supported_Model_Formats_MO_DG>
 
 .. meta::
    :description: Model conversion (MO) furthers the transition between training and

diff --git a/...atures/mo_ovc_transition/legacy_conversion_api/convert_python_model_objects.rst b/...atures/mo_ovc_transition/legacy_conversion_api/convert_python_model_objects.rst
@@ -1,8 +1,13 @@
 .. {#openvino_docs_MO_DG_Python_API}
 
-Convert Models Represented as Python Objects
-============================================
+[LEGACY] Convert Models Represented as Python Objects
+=============================================================
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Model Preparation <openvino_docs_model_processing_introduction>` article. 
 
 Model conversion API is represented by ``convert_model()`` method in openvino.tools.mo namespace. ``convert_model()`` is compatible with types from openvino.runtime, like PartialShape, Layout, Type, etc.
 

diff --git a/...nvino_legacy_features/mo_ovc_transition/legacy_conversion_api/cutting_model.rst b/...nvino_legacy_features/mo_ovc_transition/legacy_conversion_api/cutting_model.rst
@@ -1,8 +1,11 @@
 .. {#openvino_docs_MO_DG_prepare_model_convert_model_Cutting_Model}
 
-Cutting Off Parts of a Model
-============================
+[LEGACY] Cutting Off Parts of a Model
+================================================
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
 
 Sometimes, it is necessary to remove parts of a model when converting it to OpenVINO IR. This chapter describes how to do it, using model conversion API parameters. Model cutting applies mostly to TensorFlow models, which is why TensorFlow will be used in this chapter's examples, but it may be also useful for other frameworks.
 

diff --git a/...mo_ovc_transition/legacy_conversion_api/embedding_preprocessing_computation.rst b/...mo_ovc_transition/legacy_conversion_api/embedding_preprocessing_computation.rst
@@ -1,8 +1,13 @@
 .. {#openvino_docs_MO_DG_Additional_Optimization_Use_Cases}
 
-Embedding Preprocessing Computation
-===================================
+[LEGACY] Embedding Preprocessing Computation
+=====================================================
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Conversion Parameters <openvino_docs_OV_Converter_UG_Conversion_Options>` article. 
 
 Input data for inference can be different from the training dataset and requires
 additional preprocessing before inference. To accelerate the whole pipeline including

diff --git a/...no_legacy_features/mo_ovc_transition/legacy_conversion_api/fp16_compression.rst b/...no_legacy_features/mo_ovc_transition/legacy_conversion_api/fp16_compression.rst
@@ -1,9 +1,14 @@
 .. {#openvino_docs_MO_DG_FP16_Compression}
 
-Compressing a Model to FP16
-===========================
+[LEGACY] Compressing a Model to FP16
+=============================================
 
+.. danger::
 
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Conversion Parameters <openvino_docs_OV_Converter_UG_Conversion_Options>` article. 
+
 By default, when IR is saved all relevant floating-point weights are compressed to ``FP16`` data type during model conversion.
 It results in creating a "compressed ``FP16`` model", which occupies about half of
 the original space in the file system. The compression may introduce a minor drop in accuracy,

diff --git a/...legacy_features/mo_ovc_transition/legacy_conversion_api/model_optimizer_faq.rst b/...legacy_features/mo_ovc_transition/legacy_conversion_api/model_optimizer_faq.rst
@@ -1,7 +1,7 @@
 .. {#openvino_docs_MO_DG_prepare_model_Model_Optimizer_FAQ}
 
-Model Optimizer Frequently Asked Questions
-==========================================
+[LEGACY] Model Optimizer Frequently Asked Questions
+===========================================================
 
 
 .. important::

diff --git a/...egacy_features/mo_ovc_transition/legacy_conversion_api/setting_input_shapes.rst b/...egacy_features/mo_ovc_transition/legacy_conversion_api/setting_input_shapes.rst
@@ -1,7 +1,13 @@
 .. {#openvino_docs_MO_DG_prepare_model_convert_model_Converting_Model}
 
-Setting Input Shapes
-====================
+[LEGACY] Setting Input Shapes
+====================================
+
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the  :doc:`Setting Input Shapes <openvino_docs_OV_Converter_UG_prepare_model_convert_model_Converting_Model>` article. 
 
 With model conversion API you can increase your model's efficiency by providing an additional shape definition, with these two parameters: `input_shape` and `static_shape`.
 

diff --git a/...cy_features/mo_ovc_transition/legacy_conversion_api/supported_model_formats.rst b/...cy_features/mo_ovc_transition/legacy_conversion_api/supported_model_formats.rst
@@ -1,19 +1,24 @@
 .. {#Supported_Model_Formats_MO_DG}
 
-Supported Model Formats
-=======================
+[LEGACY] Supported Model Formats
+=====================================
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Supported Model Formats <Supported_Model_Formats>` article. 
 
 .. toctree::
    :maxdepth: 1
    :hidden:
 
-   openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_TensorFlow
-   openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_ONNX
-   openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_PyTorch
-   openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_TensorFlow_Lite
-   openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_Paddle
-   openvino_docs_MO_DG_prepare_model_convert_model_tutorials
+   Converting a TensorFlow Model <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_TensorFlow>
+   Converting an ONNX Model <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_ONNX>
+   Converting a PyTorch Model <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_PyTorch>
+   Converting a TensorFlow Lite Model <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_TensorFlow_Lite>
+   Converting a PaddlePaddle Model <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_Paddle>
+   Model Conversion Tutorials <openvino_docs_MO_DG_prepare_model_convert_model_tutorials>
 
 .. meta::
    :description: Learn about supported model formats and the methods used to convert, read, and compile them in OpenVINO™.

diff --git a/...ition/legacy_conversion_api/supported_model_formats/Convert_Model_From_ONNX.rst b/...ition/legacy_conversion_api/supported_model_formats/Convert_Model_From_ONNX.rst
@@ -1,13 +1,20 @@
 .. {#openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_ONNX}
 
-Converting an ONNX Model
-========================
-
+[LEGACY] Converting an ONNX Model
+=============================================
 
 .. meta::
    :description: Learn how to convert a model from the 
                  ONNX format to the OpenVINO Intermediate Representation.
 
+
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Converting an ONNX Model <openvino_docs_OV_Converter_UG_prepare_model_convert_model_Convert_Model_From_ONNX>` article. 
+
+
 .. note:: ONNX models are supported via FrontEnd API. You may skip conversion to IR and read models directly by OpenVINO runtime API. Refer to the :doc:`inference example <openvino_docs_OV_UG_Integrate_OV_with_your_application>` for more details. Using ``convert_model`` is still necessary in more complex cases, such as new custom inputs/outputs in model pruning, adding pre-processing, or using Python conversion extensions.
 
 Converting an ONNX Model

diff --git a/...ion/legacy_conversion_api/supported_model_formats/Convert_Model_From_Paddle.rst b/...ion/legacy_conversion_api/supported_model_formats/Convert_Model_From_Paddle.rst
@@ -1,14 +1,21 @@
 .. {#openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_Paddle}
 
-Converting a PaddlePaddle Model
-===============================
+[LEGACY] Converting a PaddlePaddle Model
+======================================================
 
 
 .. meta::
    :description: Learn how to convert a model from the 
                  PaddlePaddle format to the OpenVINO Intermediate Representation. 
 
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Converting a PaddlePaddle Model <openvino_docs_OV_Converter_UG_prepare_model_convert_model_Convert_Model_From_Paddle>` article.
+
+
 This page provides general instructions on how to convert a model from a PaddlePaddle format to the OpenVINO IR format using Model Optimizer. The instructions are different depending on PaddlePaddle model format.
 
 .. note:: PaddlePaddle models are supported via FrontEnd API. You may skip conversion to IR and read models directly by OpenVINO runtime API. Refer to the :doc:`inference example <openvino_docs_OV_UG_Integrate_OV_with_your_application>` for more details. Using ``convert_model`` is still necessary in more complex cases, such as new custom inputs/outputs in model pruning, adding pre-processing, or using Python conversion extensions.

diff --git a/...on/legacy_conversion_api/supported_model_formats/Convert_Model_From_PyTorch.rst b/...on/legacy_conversion_api/supported_model_formats/Convert_Model_From_PyTorch.rst
@@ -1,14 +1,20 @@
 .. {#openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_PyTorch}
 
-Converting a PyTorch Model
-==========================
+[LEGACY] Converting a PyTorch Model
+============================================
 
 
 .. meta:: 
    :description: Learn how to convert a model from the 
                  PyTorch format to the OpenVINO Intermediate Representation. 
 
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Converting a PyTorch Model <openvino_docs_OV_Converter_UG_prepare_model_convert_model_Convert_Model_From_PyTorch>` article. 
+
 This page provides instructions on how to convert a model from the PyTorch format to the OpenVINO IR format.
 
 The conversion is a required step to run inference using OpenVINO API.

diff --git a/...legacy_conversion_api/supported_model_formats/Convert_Model_From_TensorFlow.rst b/...legacy_conversion_api/supported_model_formats/Convert_Model_From_TensorFlow.rst
@@ -1,13 +1,18 @@
 .. {#openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_TensorFlow}
 
-Converting a TensorFlow Model
-=============================
-
+[LEGACY] Converting a TensorFlow Model
+============================================
 
 .. meta::
    :description: Learn how to convert a model from a 
                  TensorFlow format to the OpenVINO Intermediate Representation.
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Converting a TensorFlow Model <openvino_docs_OV_Converter_UG_prepare_model_convert_model_Convert_Model_From_TensorFlow>` article. 
+
 
 .. note:: TensorFlow models are supported via :doc:`FrontEnd API <openvino_docs_MO_DG_TensorFlow_Frontend>`. You may skip conversion to IR and read models directly by OpenVINO runtime API. Refer to the :doc:`inference example <openvino_docs_OV_UG_Integrate_OV_with_your_application>` for more details. Using ``convert_model`` is still necessary in more complex cases, such as new custom inputs/outputs in model pruning, adding pre-processing, or using Python conversion extensions.
 

diff --git a/...y_conversion_api/supported_model_formats/Convert_Model_From_TensorFlow_Lite.rst b/...y_conversion_api/supported_model_formats/Convert_Model_From_TensorFlow_Lite.rst
@@ -1,13 +1,18 @@
 .. {#openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_TensorFlow_Lite}
 
-Converting a TensorFlow Lite Model
-==================================
+[LEGACY] Converting a TensorFlow Lite Model
+=====================================================
 
 
 .. meta::
    :description: Learn how to convert a model from a 
                  TensorFlow Lite format to the OpenVINO Intermediate Representation.
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Converting a TensorFlow Lite Model <openvino_docs_OV_Converter_UG_prepare_model_convert_model_Convert_Model_From_TensorFlow_Lite>` article.
 
 To convert a TensorFlow Lite model, use the ``mo`` script and specify the path to the input ``.tflite`` model file:
 

diff --git a/...ition/legacy_conversion_api/supported_model_formats/convert_model_tutorials.rst b/...ition/legacy_conversion_api/supported_model_formats/convert_model_tutorials.rst
@@ -1,7 +1,7 @@
 .. {#openvino_docs_MO_DG_prepare_model_convert_model_tutorials}
 
-Model Conversion Tutorials
-==========================
+[LEGACY] Model Conversion Tutorials
+====================================================
 
 
 .. toctree::
@@ -39,6 +39,12 @@ Model Conversion Tutorials
    :description: Get to know conversion methods for specific TensorFlow, ONNX, PyTorch, MXNet, and Kaldi models.
 
 
+.. danger::
+
+   The code described in the tutorials has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Python tutorials <tutorials>`.
+
 This section provides a set of tutorials that demonstrate conversion methods for specific 
 TensorFlow, ONNX, and PyTorch models. Note that these instructions do not cover all use 
 cases and may not reflect your particular needs.

diff --git a/..._model_formats/convert_model_tutorials/Convert_AttentionOCR_From_Tensorflow.rst b/..._model_formats/convert_model_tutorials/Convert_AttentionOCR_From_Tensorflow.rst
@@ -10,6 +10,12 @@ Converting a TensorFlow Attention OCR Model
                  OpenVINO Intermediate Representation.
 
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Python tutorials <tutorials>`.
+
 This tutorial explains how to convert the Attention OCR (AOCR) model from the `TensorFlow Attention OCR repository <https://github.com/emedvedev/attention-ocr>`__ to the Intermediate Representation (IR).
 
 Extracting a Model from ``aocr`` Library

diff --git a/...upported_model_formats/convert_model_tutorials/Convert_BERT_From_Tensorflow.rst b/...upported_model_formats/convert_model_tutorials/Convert_BERT_From_Tensorflow.rst
@@ -9,6 +9,12 @@ Converting a TensorFlow BERT Model
                  from TensorFlow to the OpenVINO Intermediate Representation.
 
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Python tutorials <tutorials>`.
+
 Pretrained models for BERT (Bidirectional Encoder Representations from Transformers) are
 `publicly available <https://github.com/google-research/bert>`__.
 

diff --git a/...ersion_api/supported_model_formats/convert_model_tutorials/Convert_Bert_ner.rst b/...ersion_api/supported_model_formats/convert_model_tutorials/Convert_Bert_ner.rst
@@ -8,6 +8,11 @@ Converting a PyTorch BERT-NER Model
    :description: Learn how to convert a BERT-NER model
                  from PyTorch to the OpenVINO Intermediate Representation.
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Python tutorials <tutorials>`.
 
 The goal of this article is to present a step-by-step guide on how to convert PyTorch BERT-NER model to OpenVINO IR. First, you need to download the model and convert it to ONNX.
 

diff --git a/...upported_model_formats/convert_model_tutorials/Convert_CRNN_From_Tensorflow.rst b/...upported_model_formats/convert_model_tutorials/Convert_CRNN_From_Tensorflow.rst
@@ -9,6 +9,12 @@ Converting a TensorFlow CRNN Model
                  from TensorFlow to the OpenVINO Intermediate Representation.
 
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Python tutorials <tutorials>`.
+
 This tutorial explains how to convert a CRNN model to OpenVINO™ Intermediate Representation (IR).
 
 There are several public versions of TensorFlow CRNN model implementation available on GitHub. This tutorial explains how to convert the model from

diff --git a/...supported_model_formats/convert_model_tutorials/Convert_Cascade_RCNN_res101.rst b/...supported_model_formats/convert_model_tutorials/Convert_Cascade_RCNN_res101.rst
@@ -9,6 +9,12 @@ Converting a PyTorch Cascade RCNN R-101 Model
                  model from PyTorch to the OpenVINO Intermediate Representation.
 
 
+.. danger::
+
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Python tutorials <tutorials>`.
+
 The goal of this article is to present a step-by-step guide on how to convert a PyTorch Cascade RCNN R-101 model to OpenVINO IR. First, you need to download the model and convert it to ONNX.
 
 Downloading and Converting Model to ONNX

diff --git a/...ed_model_formats/convert_model_tutorials/Convert_DeepSpeech_From_Tensorflow.rst b/...ed_model_formats/convert_model_tutorials/Convert_DeepSpeech_From_Tensorflow.rst
@@ -8,7 +8,12 @@ Converting a TensorFlow DeepSpeech Model
    :description: Learn how to convert a DeepSpeech model 
                  from TensorFlow to the OpenVINO Intermediate Representation.
 
+.. danger::
 
+   The code described here has been **deprecated!** Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but **you should not use** it in contemporary applications.
+
+   This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the :doc:`Python tutorials <tutorials>`.
+
 `DeepSpeech project <https://github.com/mozilla/DeepSpeech>`__ provides an engine to train speech-to-text models.
 
 Downloading the Pretrained DeepSpeech Model