Sustainment of commercial aircraft gas turbine engines in the form of maintenance, repair and overhaul (MRO) is a primary activity in the life-cycle of a modem commercial aircraft system. About forty percent of a typical air carrier's maintenance costs are due to engine MRO. As such, the MRO industry is constantly looking for opportunities to reduce costs and make sustaining aircraft over long lifetimes an affordable proposition for air carriers. Current MRO decision support tools focus on engine condition monitoring and fault diagnostic systems, and most of the existing literature has focused on developing algorithms for these systems. However, few researchers have suggested how to design a broader set of computer-based decision support tools to meet various other cognitive needs of the engine MRO community. Besides engine condition monitoring and fault diagnostics, other cognitive needs can be found in areas such as fault prognostics, maintenance planning, workscope generation and configuration management.This thesis presents a novel cognitive engineering approach to creating a framework that more fully captures the decision support needs of commercial aircraft gas turbine engine maintenance, repair and overhaul (MRO) organizations. Using field studies of various airlines, engine MRO providers and engine manufacturers across North America, AsiaPacific and Europe, the analyses presented offers a thorough understanding of these cognitive needs and the decision-making process in engine MRO. A set of preliminary recommendations are proposed for a design framework of new decision support tools for engine sustainment and how such tools can be implemented in future engine MRO operations.