Abstract: Exercise-induced fatigue is a physiological state in which the body is temporarily unable to sustain a certain level of exercise intensity or performance during or after physical activity. An accurate evaluation of exercise-induced fatigue is essential for preventing sports injuries, enhancing athletic performance, and mitigating safety incidents. Machine learning (ML) has effectively improved the accuracy and automation of fatigue evaluation by processing and modeling complex multi-dimensional data. This article provides a brief overview of the evaluation methods for exercise-induced fatigue, with a particular focus on reviewing the role and application directions of ML in the assessment of exercise-induced fatigue, aiming to offer references for optimizing fatigue management and enhancing athletic performance.