This thesis deals with the study of optimal control of McKean-Vlasov dynamics and its applications in mathematical finance. This thesis contains two parts. In the first part, we develop the dynamic programming (DP) method for solving McKean-Vlasov control problem. Using suitable admissible controls, we propose to reformulate the value function of the problem with the law (resp. conditional law) of the controlled state process as sole state variable and get the flow property of the law (resp. conditional law) of the process, which allow us to derive in its general form the Bellman programming principle. Then by relying on the notion of differentiability with respect to probability measures introduced by P.L. Lions [Lio12], and Itô’s formula...