A key component of defense acquisition programs operating using the Integrated Defense Acquisition, Technology, and Logistics Life Cycle Management System is the reliance on the triple constraints of cost, schedule, and performance. While the use of Modeling and Simulation tools and capabilities is prevalent and well established in the Research and Development, Analysis, and Training domains, acquisition programs have been reluctant to use Modeling and Simulation in any great depth due to inaccessibility of tools, Subject Matter Experts, and implications to cost and schedule. This presents a unique Simulation Management challenge which requires an in-depth understanding of the technical capabilities available within an organization, their applicability to support immediate needs, and the flexibility to utilize these capabilities within the programmatic environment to provide a value added service. The focus of this dissertation is to study the use of Modeling and Simulation in the Defense arena, and to review the applicability of Modeling and Simulation within programmatic acquisition environments which are constrained by cost, schedule, and performance. This research draws comparisons between Modeling and Simulation to other Process Improvement initiatives, such as Lean and Six Sigma, and reviews case studies involving the application of Modeling and Simulation within triple constrained environments. The development of alternate scenarios allows cost benefit analysis to be conducted for each scenario and alternate scenario, developing a case for whether or not the application of Modeling and Simulation within the triple constrained environment delivered any consequential benefit to the acquisition process. Observations are made regarding the level of Modeling and Simulation as applied within each case study, and generalized recommendations are made for the inclusion of cost benefit iv analysis methodologies for analyzing proposed Modeling and Simulation activities within acquisition programs. Limitations and shortcomings of the research activity are discussed, along with recommendations for potential future work in the Simulation Management field, both with respect to the specific case studies reviewed in this study and the general field.