Efficient prediction structure for multi-view high efficiency video coding (MV-HEVC) is a key factor in determining performance such as compression efficiency, random access, and scalability. At present, MV-HEVC reference software provided by the international standard organization JCT-3V adopts a fixed inter-view prediction structure, which makes it difficult to adaptively adjust the prediction structure. Therefore, this paper proposes a novel predictive structure algorithm based on multi-objective optimization for MV-HEVC. This paper, the design of MV-HEVC prediction structure is regarded as a multi-objective optimization problem. The idea of this paper is to first determine the position of the I-view based on the similarity analysis between the viewpoints. Then, considering the coding efficiency and the random access of the user, the multi-objective optimization function is established to solve the coded B-viewpoint between the I-viewpoint and the P-viewpoint. In the end, this paper flexibly adjusts the interview prediction structure according to the prediction structure coding parameters to improve the coding performance. Experiments show that compared with MV-HEVC, the proposed algorithm not only improves the coding efficiency but also has better the random access performance.