Abstract: In this paper，a non-balanced binary tree is proposed for extending support vector machines（SVM） to multi-class problems.The non-balanced binary tree is constructed based on the prior distribution of samples，which can make the more separable classes separated at the upper node of the binary tree.For an N class problem，this method only needs N-1 SVM classifiers in the training phase，while it has less than N binary test when making a decision.Further，this method can avoid the unclassifiable regions that exist in the conventional SVMs.The experimental result indicates that maintaining comparable accuracy，this method is faster than other methods in classification.