In this paper, we propose a new method for mining class-association rules using a tree structure. Firstly, we design a tree structure for storing frequent itemsets of datasets. Some theorems for pruning nodes and computing information in the tree are then developed. We then propose an efficient algorithm for mining CARs based on them. Experimental results show that our approach is more efficient than those used previously.