diff --git a/docs/source/cpp_api/preprocessing.rst b/docs/source/cpp_api/preprocessing.rst
index 5fd8cfe778..417c8faf7e 100644
--- a/docs/source/cpp_api/preprocessing.rst
+++ b/docs/source/cpp_api/preprocessing.rst
@@ -9,5 +9,6 @@ Preprocessing
    :maxdepth: 2
    :caption: Contents:
 
+   preprocessing_pca.rst
    preprocessing_quantize.rst
    preprocessing_spectral_embedding.rst
diff --git a/docs/source/cpp_api/preprocessing_pca.rst b/docs/source/cpp_api/preprocessing_pca.rst
new file mode 100644
index 0000000000..8a6b7ecfe0
--- /dev/null
+++ b/docs/source/cpp_api/preprocessing_pca.rst
@@ -0,0 +1,27 @@
+PCA
+===
+
+Principal Component Analysis (PCA) is a linear dimensionality reduction technique that projects data onto orthogonal directions of maximum variance.
+
+.. role:: py(code)
+   :language: c++
+   :class: highlight
+
+``#include <cuvs/preprocessing/pca.hpp>``
+
+namespace *cuvs::preprocessing::pca*
+
+Params
+----------
+
+.. doxygenstruct:: cuvs::preprocessing::pca::params
+    :project: cuvs
+    :members:
+
+PCA
+---------
+
+.. doxygengroup:: pca
+    :project: cuvs
+    :members:
+    :content-only: