Antibody affinity maturation is a key process in adaptive immunity: it’s a mechanism which allows B-cells to produce high affinity antibodies against a specific antigen. Besides the biological motivations, the analysis of this learning process brought us to build a mathematical model which could be relevant to model other evolutionary systems, but also gossip or virus propagation. Our aim is to propose and analyze a mathematical model of the division-mutation-selection process of B-cells during an immune response. In particular, we investigate how the combination of various mutation models influences the typical time-scales characterizing the efficiency of the state space exploration. Our method is based on the complementarity between probabilistic tools and numerical simulations.