Tumor T cell antigens (TTCAs) plays an important role in the field of tumor rejection and immunotherapeutic cancer. Correct identification and cataloging of TTCAs that aid tumor rejection will allow the development of highly effective personalized cancer vaccine immunotherapies and understand the protection mechanism. iTTCA-RF, a primary sequence-based predictor proposed for identifying TTCAs presented in MHC I. More specifically, we have developed a Random Forest prediction model using hybrid feature (consisting of amino acid composition, global protein sequence descriptors and grouped amino acid and peptide composition). It shows superior results in independent test set.