Abstract: Heterostructured metallic materials can maintain good toughness,and have high strength because of their special microstructures, but their complex structural parameters make it very difficult to predict their properties and design their structures. Machine learning (ML) is a powerful tool for the property prediction and structure design of heterostructured metallic materials due to its ability to deal with complex nonlinear relationships between high dimensional physical quantities. The characteristics of heterostructured metallic materials are introduced. ML algorithm and the related data processing problems are summarized. The application status of ML in the property prediction and structure design of heterostructured metallic materials is reviewed. The key problems existing in the property prediction and structure design of heterostructured metallic materials assisted by ML are given out, and the future research direction is prospected.