An algorithm of recognition and classification of three-dimensional (3D) model based on deep voxel convolution neural network is proposed. The voxelization technology is used to transform 3D polygon mesh model into a voxel matrix, and the deep features of the matrix are extracted by the deep voxel convolution neural network to enhance the expressive ability and difference of the features. The experimental results on ModelNet40 dataset show that the accuracy of the algorithm can reach about 87% for recognizing and classifying 3D mesh model. The constructed deep voxel convolution neural network can effectively enhance the feature extraction and expression ability of 3D model, as well as improve the classification accuracy of large-scale complex 3D mesh models, which is better than the current mainstream methods.