Real-time short-term travel time prediction is a critical component of the Intelligent Transportation System (ITS) and an important element of the Advanced Traveler Information System (ATIS). Accurate and reliable travel time prediction enables both user and system controller to be well informed of the likely future conditions on roadways, so that pre-trip plans and traffic control strategies can be made accordingly in order to reduce travel time and relieve traffic congestion. With these travel time predictions, roads may be used more efficiently with better overall network performance. This research will study short-term travel time prediction for freeway applications using various sources of real time travel time data. The integrated prediction model proposed here will put emphasis on travel time prediction under various traffic and weather scenarios and especially inclement weather conditions.