Bayesian multi-classifier model are the suitable model to deal with the problem of vector sequence images information retrieval, because they are the appropriate tools to store the conditional probabilities and limited meanings among terms and compute the similarity between user query and sequence images. In order to improve the speed and precision of human face image retrieval in the forensics system, a forensics system of vector human face based on Bayesian multi-classifier is proposed and designed. The overall structure, the main module design, and key technologies are given. In the experiment, trained data are generated from the limited static human face images, and tested data are originated from the video frequency image sequence. The experimental results show that the system has both quick recognition speed and high forensics capacity with the good capability of fault tolerance, and the method gains the good performance on vector face classification, and it provides a certain basis for classifying human face image both dynamically and statically.