Peptide-based immunotherapy strategies appear promising as an approach to successfully induce an antitumor immune response and prolong survival in patients with various cancers. Protein antigens and their specific epitopes are formulation targets for anti-tumor vaccines. Bioinformatical approaches to predict major histocompatibility complex binding peptides can facilitate the resource-consuming effort of T cell epitope identification. Proliferating cell nuclear antigen including Ki-67 and PCNA, associated with the proliferation process of the cell, seems to be an attractive new target for tumor-specific immunotherapy. In this study, we predicted seven HLA-A*0201-restricted CTL candidate epitope of Ki-67 and eight epitope of PCNA by computer algorithm SYFPEITHI, BIMAS, and IEDB_ANN. Subsequently, biological functions of these peptides were tested by experiments in vitro. We found Ki-67((280-288)) (LQGETQLLV) had the strongest binding-affinity with HLA-A*0201. Further study revealed that Ki-67((280-288)) increased the frequency of IFN-γ-producing T cells compared to a negative peptide. Because Ki-67 was broadly expressed in most advanced malignant tumors, indicating a potential anti-tumor application in the future.