Wuchang rice is a geographical indication product in China. Due to its high quality and low production, the phenomenon of fake is more and more serious. An effective identification method of Wuchang rice is urgent needed, for the maintenance of its brand image and interest of consumers. Base on the content of inorganic elements which are analyzed by ICP-AES and ICP-MS in rice, the identification model of Wuchang rice is studied combining with principal component analysis (PCA), Fisher discrimination and artificial neural network (ANN) in this paper. The effect on the identification of samples is poor through PCA, while the samples from Wuchang area and other areas can be identified accurately through Fisher discrimination and ANN. The average accurate identification ratio of training and verification set through Fisher discrimination is 93.5%, while the average accurate identification ratio through ANN is 96.4%. The ability to identify of ANN is better than Fisher discrimination. Wuchang rice can be identified accurately through the result of this research which provides a technology for the protection of geographical indications of this product.