The belief entropy has high performance in handling uncertain information, which is the extension of information entropy in Dempster-shafer evidence theory. The Tsallis entropy is an extent of information entropy, which is a nonextensive entropy. However, how to applied the idea of belief entropy to improve the Tsallis entropy is still an open issue. This paper proposes the nonextensive belief entropy(NBE), which consists of belief entropy and Tsallis entropy. If the extensive constant of the proposed model equal to 1, then the NBE will degenerate into classical belief entropy. Furthermore, When the basic probability assignment degenerates into probability distribution, then the proposed entropy will be degenerated as classical Tsallis entropy. Meanwhile, if NBE focus on the probability distribution and the extensive constant equal to 1, then the NBE is equate the classical information entropy. Numerical examples are applied to prove the efficiency of the proposed entropy. The experimental results show that the proposed entropy can combine the belief entropy and Tsallis entropy effectively and successfully.