Survivability of military and civilian assets is a critical issue across the armed services, prompting the need for new technologies in automating the process of identifying, assessing, and targeting a threat to support combat operations. The overall effectiveness of combat operations in achieving mission objectives constitutes the Combat Assessment (CA). CA itself supports a Command and Control (C2) system that allows the Joint Services to assess the effectiveness of on-going target strikes. An integral part of CA is Battle Damage Assessment (BDA). Traditionally, analysts reviewed multiple sources of data and prepared written assessments of the best guess as to the damage and the need for re-strikes. Using new hybrid Artificial Intelligent (AI) techniques, an Integrated Battle Damage Assessment System (IBDAS) is a rapidly re-configurable and maintainable decision support architecture that can correlate large amounts of asynchronous data from disparate data sources in near real time. This paper describes key aspects of the reasoning used in the program that have applicability to other decision aid systems.