The invention discloses a fast method for HEVC (High Efficiency Video Coding) block size partition based on a Bayes decision. The fast method comprises the following steps: first of all, dividing a video sequence into an online learning stage and a fast partitioning stage by employing scene change detection based on an average gray scale difference; then, for the online learning stage and a video frame which occurs a scene change, in each partitioning depth, respectively extracting Jinter and Jintra of a CU (Coding Unit) as characteristic values, thereby establishing a mixed Gaussian model, wherein specific parameters of the model are determined according to an EM algorithm initialized by a K-Means algorithm; and for a to-be-partitioned CU in the fast partitioning stage, extracting the characteristic values and finding a conditional probability on whether to partition according to the mixed Gaussian model, and at last, finding the decision with a relatively small risk by employing a Bayes formula of a minimum risk to take as a judgment basis on whether the current CU is partitioned. According to the fast method disclosed by the invention, the algorithm complexity is reduced, and the coding time can be greatly reduced.