The wide variations in patient demographics and concomitant injuries make the prediction of which patients will regain strength quickly following anterior cruciate ligament (ACL) reconstruction challenging. This study aimed to identify the dominant factor affecting quadriceps strength recovery after ACL reconstruction with a hamstring tendon autograft and to construct a predictive model for quadriceps strength recovery using decision tree analysis. Three hundred and eighty-six patients who underwent ACL reconstruction with a hamstring tendon autograft were included in this study. The isokinetic quadriceps strength at 60°/s was measured preoperatively and at 6 months after surgery. The quadriceps strength index (QSI) was calculated by normalising the peak torque of the involved leg with the uninvolved leg and multiplying it by 100. A stepwise multiple linear regression and a decision tree analysis were performed to assess whether or not the following parameters affect quadriceps strength recovery at 6 months: socio-demographic data and maximum isokinetic quadriceps strength. The preoperative QSI, age, and pre-injury Tegner activity scale were independently correlated with quadriceps strength recovery at 6 month after surgery. The decision tree analysis demonstrated that patients were expected to have a QSI ≥85% at 6 months after surgery if they met one of the following conditions: (1) age <23 years with a preoperative QSI ≥78.8%, (2) age ≥29 years with a preoperative QSI ≥98.0%, or (3) age <16 years with a preoperative QSI <58.5% and pre-injury Tegner activity scale ≥9. By contrast, patients ≥29 years with a preoperative QSI <98.0% were likely to achieve a quadriceps strength index <70% at 6 months after surgery. Based on the results of the decision tree analysis, younger patients could achieve good quadriceps recovery even if they have a lower preoperative QSI, whereas patients ≥29 years need a higher preoperative QSI to obtain good muscle recovery. Copyright © 2018 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.