The quality of software is one of the most critical concerns in software development. As quality assessment of a software product is harder than that of other industrial products, many fail to meet the quality objectives when completed. The software quality is highly affected by the development process actual dynamics. This thesis proposes a simulation model based on the Markov Decision Process (MDP) for quality assessment of software products since MDP is a useful technique to abstact the model of the development process dynamics and to test their impact on quality. It aims to show how the simulation techniques can be used to assess software quality at the early stages of project development. The proposed approach is based on the stochastic nature of the software development process, including project architecture, team assignment and Software Quality Assurance (SQA) system construction strategy, and qualification actions selected in the SQA system. The simulation model accepts these factors as inputs, and generates a relative quality degree as its output. The results prove its robustness and capability in identifying appropriate policies in terms of quality, cost and time.