Our focus is on the study of optimal control problem for branching diffusion processes. Initially, we introduce the problem in its strong formulation and expand it to include linearly growing drifts. To ensure its proper definition, we establish bounds on the moments of these processes. We present a relaxed formulation that provides a suitable characterization based on martingale measure. We introduce the notion of atomic control and demonstrate their equivalence to strong controls in the relaxed setting. We establish the equivalence between the strong and relaxed problem, under a Filippov-type convexity condition. Furthermore, by defining a control rule, we can restate the problem as the minimization of a lower semi-continuous function over a compact set, leading to the existence of optimal controls both for the relaxed problem and the strong one. By utilizing a useful embedding technique, we demonstrate that the value functions solves a system of HJB equations. This, in turn, leads to the establishment of a verification theorem. We then apply this theorem to a Linear-Quadratic example and a Kinetic one.