Abstract. This paper is concerned with a combination of Random Batch Methods (RBMs) and Model Predictive Control (MPC) called RBM-MPC. In RBM-MPC, the RBM is used to speed up the solution of the finite horizon optimal control problems that need to be solved in MPC. We analyze our algorithm in the linear quadratic setting and obtain explicit error estimates that characterize the stability and convergence of the proposed method. The obtained estimates are validated in numerical experiments that also demonstrate the effectiveness of RBM-MPC.