Osteoarthritis (OA) is a common joint disorder. There are several factors that may cause OA; however, the main factor causing OA is aging. With aging, loss of cartilage in the joints causes the bones to rub against each other which damage the bones and cause pain, tenderness in the joints and reduced motion. There is no cure for OA; however, there are treatments that may reduce symptoms or slow down the degradation. Identifying patients with early OA is crucial in implementing treatments to control the progression of the disease. Improved MRI (Magnetic Resonance Imaging) techniques show abnormalities in the joints that may indicate deterioration of the cartilage at an early-stage. This study aims to classify tissues to control or degraded group correctly using five MR parameters by applying a univariate classification procedure. A likelihood ratio test was applied to classify the total of 60 training and 20 validation samples to control or degraded group. A cross validation method was used to determine the success rate of the classification procedure. The results of the classification procedure were used to compute specificity and sensitivity. Average specificity and sensitivity of 100 iterations will be presented. Furthermore, noise was added to the validation set and the same procedure was repeated.