diff --git a/docs/articles_en/openvino_workflow/model_optimization_guide/ptq_introduction/quantization_w_accuracy_control.md b/docs/articles_en/openvino_workflow/model_optimization_guide/ptq_introduction/quantization_w_accuracy_control.md
index 3216e5987d7..348fa51ee4e 100644
--- a/docs/articles_en/openvino_workflow/model_optimization_guide/ptq_introduction/quantization_w_accuracy_control.md
+++ b/docs/articles_en/openvino_workflow/model_optimization_guide/ptq_introduction/quantization_w_accuracy_control.md
@@ -91,7 +91,7 @@ If the accuracy or performance of the quantized model is not satisfactory, you c
 Examples of NNCF post-training quantization with control of accuracy metric:
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-* `Post-Training Quantization of Anomaly Classification OpenVINO model with control of accuracy metric <https://github.com/openvinotoolkit/nncf/blob/develop/examples/post_training_quantization/openvino/quantize_with_accuracy_control>`__
+* `Post-Training Quantization of Anomaly Classification OpenVINO model with control of accuracy metric <https://github.com/openvinotoolkit/nncf/blob/develop/examples/post_training_quantization/openvino/anomaly_stfpm_quantize_with_accuracy_control>`__
 * `Post-Training Quantization of YOLOv8 OpenVINO Model with control of accuracy metric <https://github.com/openvinotoolkit/nncf/blob/develop/examples/post_training_quantization/openvino/yolov8_quantize_with_accuracy_control>`__
 
 See also