This study analyzed contributing factors affecting leg injury severity in pedestrian-vehicle crashes. A Binary Logistic Regression (BLR) method was used to identify the factors. Independent variables include characteristics for pedestrian, vehicle, road, and environmental conditions. The leg injury severity is classified into two classes, which are dependent variables in this study, such as 'severe' and 'minor' injuries. Pedestrian age, collision speed, and the height of vehicle were identified as significant factors for the leg injury. The probabilistic outcome of predicting leg injury severity can be effectively used in not only deriving pedestrian-related safety policies but also developing advanced vehicular technologies for pedestrian protection.