The anterior cruciate ligament(ACL) is an important stabilizer of knee joint. The ACL injury of knee is common and a serious ACL injury leads to ligament reconstruction surgery. Gait analysis is essential to identify knee condition of patients who display abnormal gait. The purpose of this study is to evaluate and classify knee condition of ACL deficient patients using a nonlinear dynamic method. The nonlinear method focuses on understanding how variations in the gait pattern change over time. The experiments were carried out for 17 subjects(l2 healthy subjects and five subjects with unilateral deficiency) walking on a motorized treadmill for 100 seconds. Three dimensional kinematics of the lower extremity were collected by using four cameras and KWON 3D motion analysis system. The largest Lyapunov exponent calculated from knee joint flexion-extension time series was used to quantify knee stability. The results revealed the difference between healthy subjects and patients. The deficient knee was significantly unstable compared with the contralateral knee. This study suggests an evaluation scheme of the severity of injury and the level of recovery. The proposed Lyapunov exponent can be used in rehabilitation and diagnosis of recoverable patients.