In this paper, a text classification method combined weighted feature vector space model and the RBPNN are presented. According to the insufficient of traditional text feature extraction method. In the method, the weigthing about text feature is given by the text feature location information and category information, and then the feature frequency is obtained. The characteristic value is calculated using the TFIDF function after that, and the characteristic vector of text is formed. Then the weights between the second network hidden layer and output layer are decided by the least squcre algorithm, so the classification model is built. The experimental results showed that, the good recall and precision are obtained. The performance of text classification method proposed is well.