With the widespread use of deep learning and the popularity of smart mobile devices, it has become a new trend that migrates deep learning applications to mobile devices. This study designs a bird identification system based on Android platform and lightweight convolutional neural network. The system does not rely on any external computing and storage resources. This study also proposes three model stacking methods based on lightweight convolutional neural network as the basic model, which is weighted average, bilinear stacking, and multi-picture and single model stacking. In this paper, we introduce three stacking methods’ structure, advantages, and disadvantages in detail. And we also give some selection methods of hyperparameters through experiments. The experimental results show that the model stacking is much better than the single model, and the accuracy of the model has been significantly improved, which can be better applied to Android mobile devices.