Effective training devices are those that meet training requirements at minimum cost, or provide the maximum training benefit for a given cost. The Optimization of Simulation-Based Training Systems (OSBATS) is a model that is designed to facilitate the investigation of tradeoffs involved in developing effective training device concepts. The model is based on benefit and cost approximations that are used to analyze tradeoffs between various training device features in developing a device configuration, and then conducts similar tradeoffs between different training device configurations. The development of OSBATS has been more theoretical than the typical decision support system or aid, but shares many of the attributes of the standard decision aid. The tools or modules that comprise the model address the following activities: a) the clustering of tasks for developing coherent training device configurations, b) the identification of optimal instructional features for a task cluster, c) the specification of optimal fidelity levels for a task cluster, d) the selection of the minimum training device family that meets training requirements, and e) the allocation of training resources in the family of suggested training devices. The final output of the OSBATS model is a functional description of the optimal set of efficient training devices given the tasks, training criteria, and cost constraints.