The utility problem will occur after the case-based reasoning system runs many times, and this problem results in a decrease performance, such as a large storage space, a low retrieval rapid. To solve this problem, a cases reduction algorithm based on support vector is proposed, whose core idea is to study the distribution principle of all cases, and find support vectors and then decide 3 boundaries, at last, reduce the redundant cases which are not of use to solve new problem. Experimental tests indicate that, the method reduces cases in the case-base and decrease retrieval complexity at the expense of very small classification accuracy.