The invention provides a credit overdue prediction method and system fused with machine learning, and the method comprises the steps: collecting a plurality of credit factor data, carrying out the preprocessing, carrying out the calculation and sorting of the importance of the credit factor data in a preprocessing result, and deleting redundancy, and obtaining the selected credit factor data; andconstructing a training sample based on the credit factor data, establishing and training a credit overdue prediction model by using LSTM based on the training sample, determining an optimal parameter, and performing credit overdue prediction after the optimal model is obtained. According to the invention, credit factor data is widely collected to improve comprehensiveness of credit overdue prediction; the missing training data is classified to improve the data quality; the class imbalance condition of the user is processed by using an oversampling method, and data distribution is balanced; all factors influencing credit expiration is sorted, and redundancy is eliminated, and then the reasonability of factor selection is improved; and a credit overdue prediction model is comprehensively established based on bidirectional LSTM in combination with timing sequence factors, optimal model parameters are determined through S-fold intersection, and the optimal model quality is improved.