In this study, Dr. Marx and colleagues from the MARS (Multicenter ACL Revision Study) Group developed and tested a new machine learning model to predict which patients are most at risk of failure after revision ACL reconstruction. Using data from hundreds of patients across multiple centers, the researchers analyzed a wide range of factors like age, activity level, surgical technique, and graft type to identify patterns linked to poor outcomes or the need for another surgery. The model was able to accurately predict which patients were more likely to experience a graft retear or ongoing knee instability after revision ACL surgery. This research represents an important step toward using artificial intelligence to personalize treatment planning and improve long-term results for patients undergoing complex ACL reconstructions.