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This research article aims to identify and introduce cost-saving measures for increasing the return on investment during the Software Development Life Cycle (SDLC) through selected quantitative analyses employing both the Monte Carlo Simulation and Discrete Event Simulation approaches. Through the use of modeling and simulation, the authors develop quantitative analysis for discovering financial cost and impact when meeting future demands of an organization’s SDLC management process associated with error rates. Though this sounds like an easy and open practice, it is uncommon for most competitors to provide empirical data outlining their error rates associated with each of the SDLC phases nor do they normally disclose the impact of such error rates on the overall development effort. The approach presented in this article is more plausible and scientific than the conventional wait-and-see, whatever-fate-may-bring approach with its accompanying unpleasant surprises, often resulting in wasted resources and time.