Abstract: Off-line handwritten numeric recognition is an important branch of Optical Character Recognition（OCR）.It is widely used in the fields of bank note and post code handwritten numeric recognition task.There are many difficult for improve recognition rate if use only one classify machine,so many combining classifies methods have been proposed.In this paper,through extracting the feature of the off-line handwritten numeric characters based on the feature complementary,a method of integrated multi-classifiers of complementary based on the degree of confidence is proposed,witch includes the technology of the least distance classifier,the tree classifier as well as the BP network classifier.Experimental results show that the method proposed in this paper has excellent recognition rate and speed.