In order to realize the robustness of three-Dimensional (3D) face recognition algorithm to expression variations, a multi-region template fusion 3D face recognition algorithm based on semantic alignment was proposed. Firstly, in order to guarantee the semantic alignment of 3D faces, all the 3D face models were densely aligned with a pre-defined standard reference 3D face model. Then, considering the expressions were regional, to be robust to region division, a multi-region template based similarity prediction method was proposed. Finally, all the prediction results of multiple classifiers were fused by majority voting method. The experimental results show that, the proposed algorithm can achieve the rank-1 face recognition rate of 98.69% on FRGC (the Face Recognition Grand Challenge) v2.0 expression 3D face database and rank-1 face recognition rate of 84.36% on Bosphorus database with occlusion change.