Objective: With the development of peptide-based cancer specific immunotherapy, the prediction of CTL epitopes from insulin-like growth factor-binding protein 7 (IGFBP7) is very important for some research about tumor metastasis. Because HLA-A2.1-expressing individuals cover ＞50% in the population of China, we aimed at identifying IGFBP7-encoded peptide presented by HLA-A2.1. Methods: In our study, a HLA-A2.1 restricted CTL epitope was identified by using the following two-step procedure: (a) computer-based epitope prediction from the amino acid sequence of IGFBP7 antigen; (b) Validation with epitope molecular modeling. Results: We obtained four epitopes with high immunogenicity scores by all of the three algorithms, i.e., BIMAS, SYFPEITHI and IMTECH. Each of the four candidates satisfied the criteria of the HLA-A2.1-restricted CTL epitopes in molecular modeling analysis. Conclusion: The combination of BIMAS, SYFPEITHI and IMTECH method can improve the prediction efficiency and accuracy. Due to this research herein, this four epitopes have potential value for further studied, also have potential application in peptide-mediated immunotherapy. These epitopes may be useful in the design of therapeutic peptide vaccine for lung carcinoma and as immunotherapeutic strategies against lung carcinoma after identified by immunology experiment.