Safety performance is a crucial component of highway network performance evaluation. Besides their devastating impact on roadway users, traffic crashes lead to substantial economic losses on both personal and societal levels. Due to the complexity of crash events and the unique conditions in each country and state, empirical local calibration for the correlation between attributes of interest and the safety performance is always recommended. Limited studies have established a procedure to analyze the impact of pavement condition on traffic safety in a risk analysis scheme. This study presents a thorough analysis of some roadway departure crashes which occurred in Iowa between 2006 and 2016. All crash records were mapped onto one-mile segments with known traffic volume (i.e., AADT), posted speed limits (SL), skid numbers (SN), ride qualities (IRI), and rut depths (RD) in a geographic information system (GIS) database. The crash records were correlated to the pavement surface condition (i.e., SN, IRI, and RD) using negative binomial regression models. Moreover, a novel risk analysis framework is introduced to perform crash risk assessment and evaluate the possible consequences for a given combination of events. The analysis shows a significant impact of pavement skid resistance on roadway-departure crashes under all accident conditions and severities. Risk analysis will facilitate coordination between the pavement management system and safety management system in the future, which will help with optimizing the overall highway network performance.