Microscopic analysis of pedestrian-vehicle accident data is a backbone of devising various intelligent functionalities of vehicles to mitigate the fatality and injury severity of pedestrian in pedestrian-vehicle crashes. Worldwide significant effort has been directed at developing advanced vehicles for protecting pedestrian by the assistance of analyzing very detailed pedestrian accident data. As a part of the multi-year project titled with ‘Development of Advanced Vehicle for Pedestrian Protection’, this study analyzes pedestrian-vehicle crash data. Firstly, overview of the characteristics of pedestrian-involved crashes in Korea is presented. Another major focus of the study is to develop a probabilistic pedestrian fatality model. The logistic regression approach, one of the multivariate statistical modeling techniques, is applied in the model development. The developed model is expected to support various safety policies and evaluations of advanced systems of vehicles toward enhancing pedestrian safety. The findings of this study would be an invaluable linkage between pedestrian accident data and the development of various countermeasures for pedestrian protection.