A deep learning-based model for the classification and prediction of Baijiu wine brands is developed, combining with the Tensorflow and Keras frameworks. The test sample data set is established by collecting the feature information of Baijiu wine to be tested through an electronic tongue (an array sensor), combining the known Baijiu wine categories with that of the unknow one (to be test). Then the deep learning-based Baijiu wine brand classification prediction model was trained and tested for, preparing for the performance by using the trainedand tested sets. The results showed that the prediction model achieves 99.987% of Baijiu wine brand recognition rate, showing a high accuracy.