Motivation: A lack of accurate computational tools to guide rational mutagenesis has made affinity maturation a recurrent challenge in antibody development. We previously showed that graph-based signatures can be used to predict the effects of mutations on antibody binding affinity. Results: Here we present an updated and refined version of this approach, mCSM-AB2, capable of accurately modelling the effects of mutations on antibody-antigen binding affinity, through the inclusion of evolutionary and energetic terms. Using a new and expanded database of over 1800 mutations with experimental binding measurements and structural information, mCSM-AB2 achieved a Pearson's correlation of 0.73 and 0.77 across training and blind tests, respectively, out-performing available methods currently used for rational antibody engineering. Availability and Implementation. mCSM-AB2 is available as a user-friendly and freely-accessible web server providing rapid analysis of both individual mutations or the entire binding interface to guide rational antibody affinity maturation at http://biosig.unimelb.edu.au/mcsm_ab2