Weight is an important quality characteristic of injection-molding products. The current work focuses on the online, prediction and closed-loop control of the product weight. Previous researchers used the process set-points as the inputs to establish weight prediction model. These models cannot reflect the weight variations at a given setting. In this study, an online weight prediction model has been developed, with the process variable trajectories as the inputs, using a principal component regression (PCR) model. A nonlinear enhancement has been made to improve the prediction accuracy of the PCR weight model. Based on such an online prediction, a closed-loop weight control system has been developed and tested experimentally.