The program TEpredict was developed for T-cell epitope prediction. The used models for T-cell epitope prediction were constructed by the partial least squares regression method using the data extracted from the IEDB (Immune Epitope Database), the most complete resource of experimental peptide--MHC binding data. TEpredict is also able to predict proteasomal processing of protein antigens and the ability of produced oligopeptides to bind to the transporters associated with antigen processing, to discard the peptides sharing local similarity with human proteins from the set of predicted epitopes, and to estimate the expected population coverage by the selected peptides using the data on HLA allele genotypic frequencies. The main part of the constructed models demonstrated a high prediction sensitivity (0.50--0.80) in combination with a high specificity (0.75--0.99). Comparative testing demonstrated that TEpredict was competitive with or even superior to the programs ProPred1, SVRMHC, SVMHC, and SYFPEITHI. Thus, TEpredict can become an efficient tool for developing polyepitope vaccines, including the vaccines against various human pathogens, such as HIV and the influenza virus. TEpredict and the source code are available at http://tepredict.sourceforge.net.