diff --git a/Project.toml b/Project.toml
index db31493..507b366 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,6 +1,6 @@
 name = "Distances"
 uuid = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
-version = "0.10.9"
+version = "0.10.10"
 
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
@@ -9,21 +9,27 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsAPI = "82ae8749-77ed-4fe6-ae5f-f523153014b0"
 
 [weakdeps]
+ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 
 [extensions]
+DistancesChainRulesCoreExt = "ChainRulesCore"
 DistancesSparseArraysExt = "SparseArrays"
 
 [compat]
+ChainRulesCore = "1"
 StatsAPI = "1"
 julia = "1"
 
 [extras]
+ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
+ChainRulesTestUtils = "cdddcdb0-9152-4a09-a978-84456f9df70a"
 OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
+StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
 [targets]
-test = ["OffsetArrays", "Random", "SparseArrays", "Test", "Unitful"]
+test = ["ChainRulesCore", "ChainRulesTestUtils", "OffsetArrays", "Random", "SparseArrays", "StableRNGs", "Test", "Unitful"]
diff --git a/ext/DistancesChainRulesCoreExt.jl b/ext/DistancesChainRulesCoreExt.jl
new file mode 100644
index 0000000..10d89bb
--- /dev/null
+++ b/ext/DistancesChainRulesCoreExt.jl
@@ -0,0 +1,150 @@
+module DistancesChainRulesCoreExt
+
+using Distances
+
+import ChainRulesCore
+
+const CRC = ChainRulesCore
+
+## SqEuclidean
+
+function CRC.rrule(
+    ::CRC.RuleConfig{>:CRC.HasReverseMode},
+    dist::SqEuclidean,
+    x::AbstractVector{<:Real},
+    y::AbstractVector{<:Real}
+)
+    Ω = dist(x, y)
+
+    function SqEuclidean_pullback(ΔΩ)
+        x̄ = (2 * CRC.unthunk(ΔΩ)) .* (x .- y)
+        return CRC.NoTangent(), x̄, -x̄
+    end
+
+    return Ω, SqEuclidean_pullback
+end
+
+function CRC.rrule(::CRC.RuleConfig{>:CRC.HasReverseMode}, ::typeof(colwise), dist::SqEuclidean, X::AbstractMatrix{<:Real}, Y::AbstractMatrix{<:Real})
+    Ω = colwise(dist, X, Y)
+
+    function colwise_SqEuclidean_pullback(ΔΩ)
+        X̄ = 2 .* CRC.unthunk(ΔΩ)' .* (X .- Y)
+        return CRC.NoTangent(), CRC.NoTangent(), X̄, -X̄
+    end
+
+    return Ω, colwise_SqEuclidean_pullback
+end
+
+function CRC.rrule(::CRC.RuleConfig{>:CRC.HasReverseMode}, ::typeof(pairwise), dist::SqEuclidean, X::AbstractMatrix{<:Real}; dims::Union{Nothing,Integer}=nothing)
+    dims = Distances.deprecated_dims(dims)
+    dims in (1, 2) || throw(ArgumentError("dims should be 1 or 2 (got $dims)"))
+    Ω = pairwise(dist, X; dims=dims)
+
+    function pairwise_SqEuclidean_X_pullback(ΔΩ)
+        Δ = CRC.unthunk(ΔΩ)
+        A = Δ .+ transpose(Δ)
+        X̄ = if dims == 1
+            2 .* (sum(A; dims=2) .* X .- A * X)
+        else
+            2 .* (X .* sum(A; dims=1) .- X * A)
+        end
+        return CRC.NoTangent(), CRC.NoTangent(), X̄
+    end
+
+    return Ω, pairwise_SqEuclidean_X_pullback
+end
+
+function CRC.rrule(::CRC.RuleConfig{>:CRC.HasReverseMode}, ::typeof(pairwise), dist::SqEuclidean, X::AbstractMatrix{<:Real}, Y::AbstractMatrix{<:Real}; dims::Union{Nothing,Integer}=nothing)
+    dims = Distances.deprecated_dims(dims)
+    dims in (1, 2) || throw(ArgumentError("dims should be 1 or 2 (got $dims)"))
+    Ω = pairwise(dist, X, Y; dims=dims)
+
+    function pairwise_SqEuclidean_X_Y_pullback(ΔΩ)
+        Δ = CRC.unthunk(ΔΩ)
+        Δt = transpose(Δ)
+        X̄ = if dims == 1
+            2 .* (sum(Δ; dims=2) .* X .- Δ * Y)
+        else
+            2 .* (X .* sum(Δt; dims=1) .- Y * Δt)
+        end
+        Ȳ = if dims == 1
+            2 .* (sum(Δt; dims=2) .* Y .- Δt * X)
+        else
+            2 .* (Y .* sum(Δ; dims=1) .- X * Δ)
+        end
+        return CRC.NoTangent(), CRC.NoTangent(), X̄, Ȳ
+    end
+
+    return Ω, pairwise_SqEuclidean_X_Y_pullback
+end
+
+## Euclidean
+
+_normalize(x::Real, nrm::Real) = iszero(nrm) && !isnan(x) ? one(x / nrm) : x / nrm
+
+function CRC.rrule(::CRC.RuleConfig{>:CRC.HasReverseMode}, dist::Euclidean, x::AbstractVector{<:Real}, y::AbstractVector{<:Real})
+    Ω = dist(x, y)
+
+    function Euclidean_pullback(ΔΩ)
+        x̄ = _normalize(CRC.unthunk(ΔΩ), Ω) .* (x .- y)
+        return CRC.NoTangent(), x̄, -x̄
+    end
+
+    return Ω, Euclidean_pullback
+end
+
+function CRC.rrule(::CRC.RuleConfig{>:CRC.HasReverseMode}, ::typeof(colwise), dist::Euclidean, X::AbstractMatrix{<:Real}, Y::AbstractMatrix{<:Real})
+    Ω = colwise(dist, X, Y)
+
+    function colwise_Euclidean_pullback(ΔΩ)
+        X̄ = _normalize.(CRC.unthunk(ΔΩ)', Ω') .* (X .- Y)
+        return CRC.NoTangent(), CRC.NoTangent(), X̄, -X̄
+    end
+
+    return Ω, colwise_Euclidean_pullback
+end
+
+function CRC.rrule(::CRC.RuleConfig{>:CRC.HasReverseMode}, ::typeof(pairwise), dist::Euclidean, X::AbstractMatrix{<:Real}; dims::Union{Nothing,Integer}=nothing)
+    dims = Distances.deprecated_dims(dims)
+    dims in (1, 2) || throw(ArgumentError("dims should be 1 or 2 (got $dims)"))
+    Ω = pairwise(dist, X; dims=dims)
+
+    function pairwise_Euclidean_X_pullback(ΔΩ)
+        Δ = CRC.unthunk(ΔΩ)
+        A = _normalize.(Δ .+ transpose(Δ), Ω)
+        X̄ = if dims == 1
+            sum(A; dims=2) .* X .- A * X
+        else
+            X .* sum(A; dims=1) .- X * A
+        end
+        return CRC.NoTangent(), CRC.NoTangent(), X̄
+    end
+
+    return Ω, pairwise_Euclidean_X_pullback
+end
+
+function CRC.rrule(::CRC.RuleConfig{>:CRC.HasReverseMode}, ::typeof(pairwise), dist::Euclidean, X::AbstractMatrix{<:Real}, Y::AbstractMatrix{<:Real}; dims::Union{Nothing,Integer}=nothing)
+    dims = Distances.deprecated_dims(dims)
+    dims in (1, 2) || throw(ArgumentError("dims should be 1 or 2 (got $dims)"))
+    Ω = pairwise(dist, X, Y; dims=dims)
+
+    function pairwise_Euclidean_X_Y_pullback(ΔΩ)
+        Δ = _normalize.(CRC.unthunk(ΔΩ), Ω)
+        Δt = transpose(Δ)
+        X̄ = if dims == 1
+            sum(Δ; dims=2) .* X .- Δ * Y
+        else
+            X .* sum(Δt; dims=1) .- Y * Δt
+        end
+        Ȳ = if dims == 1
+            sum(Δt; dims=2) .* Y .- Δt * X
+        else
+            Y .* sum(Δ; dims=1) .- X * Δ
+        end
+        return CRC.NoTangent(), CRC.NoTangent(), X̄, Ȳ
+    end
+
+    return Ω, pairwise_Euclidean_X_Y_pullback
+end
+
+end # module
\ No newline at end of file
diff --git a/test/chainrules.jl b/test/chainrules.jl
new file mode 100644
index 0000000..2bc44ea
--- /dev/null
+++ b/test/chainrules.jl
@@ -0,0 +1,46 @@
+using ChainRulesCore
+using ChainRulesTestUtils
+using StableRNGs
+
+@testset "ChainRulesCore extension" begin
+    n = 4
+    rng = StableRNG(100)
+    x = randn(rng, n)
+    y = randn(rng, n)
+    X = randn(rng, n, 3)
+    Y = randn(rng, n, 3)
+    Xrep = repeat(x, 1, 3)
+    Yrep = repeat(y, 1, 3)
+
+    @testset for metric in (SqEuclidean(), Euclidean())
+        # Single evaluation
+        test_rrule(metric ⊢ NoTangent(), x, y)
+        test_rrule(metric ⊢ NoTangent(), x, x)
+
+        for A in (X, Xrep)
+            # Column-wise distance
+            test_rrule(colwise, metric ⊢ NoTangent(), A, A)
+
+            # Pairwise distances
+            # Finite differencing yields impressively inaccurate derivatives for `Euclidean`,
+            # see https://github.com/FluxML/Zygote.jl/blob/45bf883491d2b52580d716d577e2fa8577a07230/test/gradcheck.jl#L1206
+            kwargs = metric isa Euclidean ? (rtol=1e-3, atol=1e-3) : ()
+            test_rrule(pairwise, metric ⊢ NoTangent(), A; kwargs...)
+            test_rrule(pairwise, metric ⊢ NoTangent(), A; fkwargs=(dims=1,), kwargs...)
+            test_rrule(pairwise, metric ⊢ NoTangent(), A; fkwargs=(dims=2,), kwargs...)
+            test_rrule(pairwise, metric ⊢ NoTangent(), A, A; kwargs...)
+            test_rrule(pairwise, metric ⊢ NoTangent(), A, A; fkwargs=(dims=1,), kwargs...)
+            test_rrule(pairwise, metric ⊢ NoTangent(), A, A; fkwargs=(dims=2,), kwargs...)
+
+            for B in (Y, Yrep)
+                # Column-wise distance
+                test_rrule(colwise, metric ⊢ NoTangent(), A, B)
+
+                # Pairwise distances
+                test_rrule(pairwise, metric ⊢ NoTangent(), A, B)
+                test_rrule(pairwise, metric ⊢ NoTangent(), A, B; fkwargs=(dims=1,))
+                test_rrule(pairwise, metric ⊢ NoTangent(), A, B; fkwargs=(dims=2,))
+            end
+        end
+    end
+end
diff --git a/test/runtests.jl b/test/runtests.jl
index 8cbeff8..c7b60ce 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -11,3 +11,11 @@ using Unitful.DefaultSymbols
 
 include("F64.jl")
 include("test_dists.jl")
+
+# Test ChainRules definitions on Julia versions that support weak dependencies
+# Support for extensions was added in
+# https://github.com/JuliaLang/julia/commit/93587d7c1015efcd4c5184e9c42684382f1f9ab2
+# https://github.com/JuliaLang/julia/pull/47695 
+if VERSION >= v"1.9.0-alpha1.18"
+    include("chainrules.jl")
+end
\ No newline at end of file