A novel character recognition method, called Character Recognition based on Neural Network and Dempster-Shafer theory (CRNNDS), is proposed in this paper. The CRNNDS integrates a Recurrent Neural Network (RNN) and Dempster-Shafer (D-S) theory to recognize handwritten characters. It employs an RNN to effectively extract oriented features of a handwritten character and then these features are applied to Dempster-Shafer theory which can powerfully estimate the similarity ratings between a recognized character and sampling characters in the character database. Experimental results demonstrate that the CRNNDS system achieves a satisfying recognition performance. Keywords: Dempster-Shafer theory; Recurrent neural network; Mass functions; Basic probability assignment; Character recognition