In this paper we present a new method for fusing classiers output for problems with a number of classes M > 2. We extend the well-known Behavior Knowledge Space method with a hierarchical ap- proach of the dierent cells. We propose to add the ranking information of the classiers output for the combination. Each cell can be divided into new sub-spaces in order to solve ambiguities. We show that this method allows a better control of the rejection, without using new classiers for the empty cells. This method has been applied on a set of classi- ers created by bagging. It has been successfully tested on handwritten character recognition allowing better-detailed results. The technique has been compared with other classical combination methods.