Ligaments are important joint stabilizers but assessing their mechanical properties remain challenging. We developed a methodology to investigate the effects of kinematic measurement uncertainty during laxity tests on optimization-based estimation of ligament properties. We applied this methodology to a subject-specific knee model with known ligament properties as inputs and compared the estimated to the known knee ligament properties under the influence of noise. Four different sets of laxity tests were simulated with an increasing number of load cases, capturing anterior/posterior, varus/valgus, and internal/external rotation loads at 0 deg and 30 deg of knee flexion. 20 samples of uniform random noise ([−0.5,0.5] mm and degrees) were added to each set and fed into an optimization routine that subsequently estimated the ligament properties based on the noise targets. We found a large range of estimated ligament properties (stiffness ranges of 5.97 kN, 7.64 kN, 8.72 kN, and 3.86 kN; reference strain ranges of 3.11%, 2.53%, 1.88%, and 1.58% for anterior cruciate ligament (ACL), posterior cruciate ligament (PCL), medical collateral ligament (MCL), and lateral collateral ligament (LCL), respectively) for three sets of laxity tests, including up to 22 load cases. A set of laxity tests with 60 load cases kept the stiffness and reference strain ranges below 470 N per unit strain and 0.85%, respectively. These results illustrate that kinematic measurement noise have a large impact on estimated ligament properties and we recommend that future studies assess and report both the estimated ligament properties and the associated uncertainties due to kinematic measurement noise.