Abstract: In order to put cigarette products into markets precisely, an intelligent cigarette release model based on LSTM (Long Short-Term Memory) and BP (Back Propagation) neural network was proposed, which included two procedures: product sales volume prediction and product release strategy generation. First, extract the time sequencing characteristics of cigarette sales volume by LSTM, and predict the sales volume by the model combining with the characteristics extracted by experts. Second, calculate the release strategy of cigarette products automatically by the model on the basis of the predicted sales volume and the artificially selected ways of product release. The model was validated with the historical sale data of the cigarettes of 189 different versions and 25 major cigarette brands manufactured by Shandong Qingdao Tobacco Company Limited. The results showed that the prediction accuracy for the sales volume of the 189 cigarette versions was 95.67% and that for the release of the 25 major cigarette brands was 92.40%. This technology provides a support for the intelligent generation of cigarette product release strategy.