These last years several research works have studied the application of Micro-Electro-Mechanical Systems (MEMS) for aerodynamical active flow control. Controlling such MEMSbased systems remains a challenge. Among the several existing control approaches for time varying systems, many of them use a process model representing the dynamic behavior of the process to be controlled. The purpose of this paper is to study the suitability of an artificial neural network first to predict the flow evolution induced by MEMS, and next to optimize the flow w.r.t a numerical criterion.