Traffic prediction generated by multimedia sources is needed for effective dynamic bandwidth allocation and for multimedia quality of services (QoS) control strategies implemented at the network edges. In this paper, an H_infin-optimal mode is proposed for video traffic prediction, which not only minimizes the worst possible effect in the estimation error but also does not require a priori knowledge of the noise source statistics. The proposed method has been applied to modeling and prediction MPEG-4 variable bit rate (VBR) video traffic. Simulation results show that the proposed model is more robust compared with the Kalman prediction model and is able to predict the original traffic more accurately, thus more suitable for real time video traffic prediction and resource reservation