The importance of B-lymphocyte-restricted differentiation antigen Bp35 (CD20) as a target for immunotherapeutic depletion of B cells is irrefutable. Several anti-human CD20 (anti-hCD20) monoclonal antibodies are expressed at different stages of development. However, resistance to anti-CD20 therapy has made the search for new alternatives imperative. Identification of B-cell epitopes within hCD20 using in silico tools can provide new opportunities to develop monoclonal antibodies with different binding sites. Furthermore, identification of the relationship between amino acid sequences of predicted B-cell epitopes and immune responses facilitates the determination of immunogenic regions of proteins by using their primary structure. Experimental evaluation of predicted linear B-cell epitopes as candidate peptides and bioinformatics allows us to explore this relationship. In this study, we selected three candidate epitopes within the extra membrane loop of hCD20 with the aid of five immunoinformatics predictor web servers and evaluated mouse humoral response to keyhole-limpet-hemocyaninconjugated peptides, and P4 and P5 peptides (the extracellular loop of hCD20 without and with a disulfide bond, respectively). Injection of the peptides yielded results that confirmed the prediction and selection of candidates. ELISA and flow cytometry corroborated the in silico selections. The B-cell epitopes P1, P2, and P3 were effective for immunization of mice.