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Watermarking based DRM implementations insert imperceptible information or watermark in digital media to trace owner of the content and deter the illegal distribution of media. In geometry based 3D watermarking algorithms, a watermark is inserted by modifying the coordinates of vertices in the mesh. It is a requirement of watermarking algorithms that this change in vertex coordinates shouldn't cause perceptible distortion. It has always been a challenge to select vertices in the 3D model which would not cause perceptible distortion on addition of watermark. This paper proposes a novel approach to overcome this challenge using Artificial Neural Networks (ANN). Feature vectors representing the geometry of the vertex and its surrounding vertices are extracted and used to train and simulate ANN. ANN is used as a classifier to determine which vertices should be selected for watermarking. Experimental results simulate various attacks to test the robustness of the algorithm.