Aimed at the problems that the prediction accuracy is low and the dependability of software reliability model is weak based on single neural network, a Real BP-AdaBoost based on weighted information entropy (WIE) is proposed. First, the Real BP-AdaBoost is established by taking BP neural network as the base classifier of Real AdaBoost. Then, the weighted method of base classifier of Real BP-AdaBoost is improved by utilizing the product of the overall weights of the classifier for training samples and individual weight of the classifier to test samples as the final weight, and the WIE Real BP-AdaBoost is produced. Finally, the proposed algorithm is compared with SVM, BP neural network, Elman neural network and Real BP-AdaBoost with respect to two real software failure data. The mean square error of WIE Real BP-AdaBoost of the forecasted two sets data is 0.442 87 and 0.284 71 respectively, both are below the mean square error of the four comparison models. The result shows that WIE Real BP-AdaBoost is higher in prediction accuracy and reliable in dependability.