Resin transfer molding (RTM) is an efficient manufacturing process for fabricating polymer composites, in which liquid thermosetting resin is injected into a closed mold to saturate a fiber preform. In RTM, effective flow control is necessary to direct the resin to flow in the desired manner and to prevent the formation of defects. Most existing methods are based on numerical flow simulations, whose accuracy is directly tied to the fidelity of the physics and material models used in the codes. The control performance of these methods largely depends on the quality of the models. The traditional proportional-integral-differential controllers are unsuitable as well, because of the nonlinear and time-varying characteristics of the RTM system. In this research, a model predictive control strategy is proposed for adjusting the flow behavior of the resin inside the mold, and it does not rely on process simulators. Recursive least squares with an adaptive directional forgetting factor is adopted as a method to identify the input-output relationship of the process under control. Based on the identification results, both the flow velocity and the flow front profile can be controlled simultaneously. The feasibility of the proposed strategy are illustrated with experimental results. POLYM. ENG. SCI., 58:1659-1665, 2018. (c) 2017 Society of Plastics Engineers