In order to improve the classification accuracy of test samples from different datasets in multi-domain image classification, this paper proposes a multi-domain sample classification method based on Baidu AI open platform image recognition and multi-model fusion. The classification task is divided into two steps: first, the domain to which the sample belongs is determined based on the predicted label and its probability output by the Baidu API, and then the deep learning model trained on that domain is used to predict the label of the sample. The effectiveness of the proposed method is verified through extensive experiments on three public datasets: Cifar-10, Cifar100, and Mini-ImageNet. In addition, compared with existing algorithms, the proposed method shows significant improvements in classification performance.