diff --git a/forestplot/mplot_graph_utils.py b/forestplot/mplot_graph_utils.py
index edd381a..e32f5df 100644
--- a/forestplot/mplot_graph_utils.py
+++ b/forestplot/mplot_graph_utils.py
@@ -112,7 +112,6 @@ def mdraw_yticklabels(
 def mdraw_est_markers(
     dataframe: pd.core.frame.DataFrame,
     estimate: str,
-    yticklabel: str,
     model_col: str,
     models: Sequence[str],
     ax: Axes,
@@ -120,7 +119,37 @@ def mdraw_est_markers(
     mcolor: Union[Sequence[str], None] = ["0", "0.4", ".8", "0.2"],
     **kwargs: Any,
 ) -> Axes:
-    """docstring"""
+    """
+    Plot scatter markers on a matplotlib Axes object based on model estimates from a DataFrame.
+
+    This function adds the scatter plot markers to an existing Axes object for different model groups in the data.
+    It allows for customization of marker symbols, colors, and sizes.
+
+    Parameters
+    ----------
+    dataframe : pd.core.frame.DataFrame
+        The pandas DataFrame containing the data to be plotted.
+    estimate : str
+        The name of the column in the DataFrame that contains the estimate values to plot on the x-axis.
+    model_col : str
+        The column in the DataFrame that defines different model groups.
+    models : Sequence[str]
+        A sequence of strings representing the different model groups to plot.
+    ax : Axes
+        The matplotlib Axes object on which the scatter plot will be drawn.
+    msymbols : Union[Sequence[str], None], optional
+        A sequence of marker symbols for each model group, defaults to 'soDx'.
+    mcolor : Union[Sequence[str], None], optional
+        A sequence of colors for each model group, defaults to ["0", "0.4", ".8", "0.2"].
+    **kwargs : Any
+        Additional keyword arguments. Supported customizations include 'markersize' (default 40)
+        and 'offset' for the spacing between markers of different model groups.
+
+    Returns
+    -------
+    Axes
+        The modified matplotlib Axes object with the scatter plot added.
+    """
     markersize = kwargs.get("markersize", 40)
     n = len(models)
     offset = kwargs.get("offset", 0.3 - (n - 2) * 0.05)
diff --git a/tests/test_mplot_graph_utils.py b/tests/test_mplot_graph_utils.py
index bcc5e9b..b7b3626 100644
--- a/tests/test_mplot_graph_utils.py
+++ b/tests/test_mplot_graph_utils.py
@@ -2,13 +2,15 @@
 import pandas as pd
 from matplotlib.pyplot import Axes
 
-from forestplot.mplot_graph_utils import mdraw_ref_xline, mdraw_yticklabels
+from forestplot.mplot_graph_utils import mdraw_est_markers, mdraw_ref_xline, mdraw_yticklabels
 
 x, y = [0, 1, 2], [0, 1, 2]
 str_vector = ["a", "b", "c"]
+models_vector = ["m1", "m1", "m2"]
 input_df = pd.DataFrame(
     {
         "yticklabel": str_vector,
+        "model": models_vector,
         "estimate": x,
         "moerror": y,
         "ll": x,
@@ -50,3 +52,20 @@ def test_mdraw_yticklabels():
 
     assert isinstance(ax, Axes)
     assert [label.get_text() for label in ax.get_yticklabels()] == str_vector
+
+
+def test_mdraw_est_markers():
+    _, ax = plt.subplots()
+    ax = mdraw_est_markers(
+        input_df,
+        estimate="estimate",
+        model_col="model",
+        models=list(set(models_vector)),
+        ax=ax,
+    )
+    assert (all(isinstance(tick, int)) for tick in ax.get_yticks())
+
+    xmin, xmax = ax.get_xlim()
+    assert xmin <= input_df["estimate"].min()
+    assert xmax >= input_df["estimate"].max()
+    assert len(ax.collections) == len(set(models_vector))