Anticancer peptides (ACPs),known as potential future therapeutics for cancer, have been studied extensively,attribution to their unique ability to target cancer cells without affecting healthy cells directly.Many peptide-based drugs are currently being evaluated in preclinical and clinical trial. In this work, we propose a novel ensemble learning framework, termed, ACPredStackL using stacking strategy for accurate identification of ACPs.