Traffic safety has been a major concern in many developing countries during the past two decades. Rapid growth in car ownership and use has extensively increased exposure to traffic crashes. Current practice regarding crashes is based mainly on short-term traffic engineering measures. However, one important issue in dealing with traffic crashes is long-range safety plans that account for future changes in transportation demand. This planning requires specialized tools and methods to forecast crash frequencies. One such tool is the aggregate (macro-level) crash prediction model. This research introduces crash generation models (CGMs), which are developed on the basis of the trip generation phase of the four-step demand modeling technique. These models are capable of forecasting the number of crashes in urban traffic analysis zones on the basis of the forecast number of trips generated by purpose. CGMs may be used for immediate checking of the effect of future trip generations on crash frequencies in comprehensive transportation planning studies (i.e., the ability to forecast crashes at each time-step when trips are being forecast). These models will help safety planners develop travel-demand management scenarios and simultaneously assess their perceived effects on the overall safety of urban areas. The models prove an effective step toward incorporating safety into long-range transportation planning.