An intelligent system is presented to objectively assess and monitor the recovery progress of subjects who have undergone anterior cruciate ligament reconstruction (ACL-R) surgery. The system acquires 3D joint motion and muscle activity data during walking and balance tests using wireless sensors. It generates an integrated feature set from the data and applies fuzzy clustering and neural network methods to provide recovery indicators such as current recovery stage and percentage of recovery compared to healthy individuals. The system was tested on data from healthy and ACL-R subjects, accurately identifying recovery stages above 95% for walking and 80% for balance. Assessments were consistent with physiotherapists' evaluations using standard subjective scores. The validated system can support clinicians' quantitative rehabilitation analysis of ACL-