The prediction of incident durations can facilitate incident management and support traveler decisions. This paper develops a procedure for predicting incident durations. First, the causal and non-causal factors which influence incident durations are conceptualized. These include operational characteristics such as response times and whether a heavy wrecker was used, incident characteristics such as injuries and number of vehicles involved and environmental conditions such as weather and visibility. Specific hypotheses are tested by developing truncated regression models of incident duration using data provided by the Illinois Department of Transportation (IDOT) on Chicago area freeways. Then, a time sequential methodology is developed to predict the incident durations as information about the incident is acquired in a Traffic Operations Center or TOC. Initially, after an incident is detected, information at a TOC is often acquired at a high rate, then information acquisition levels off and toward the end of an incident the acquired information may decay. Accordingly, the incident duration models grow in terms of their explanatory variables at first, then they are sustained during the middle stages and begin shrinking toward the end when information starts decaying. Finally, the implications of this prediction methodology are discussed.