Granzyme B (GrB) and caspases cleave specific protein substrates to induce apoptosis in virally infected and neoplastic cells. While substrates for both types of proteases have been determined experimentally, there are many more yet to be discovered in humans and other metazoans. Here, we present a bioinformatics method based on support vector machine (SVM) learning that identifies sequence and structural features important for protease recognition of substrate peptides and then uses these features to predict novel substrates. Our approach can act as a convenient hypothesis generator, guiding future experiments by high-confidence identification of peptide-protein partners.