Choosing the right tools and machines is a primary concern within process planning systems. Yet, navigating through the assortment of tools and machines is a crucial process that unfolds between scheduling and process planning. Computer-Aided Process Planning (CAPP) systems require a high degree of flexibility to effectively manage rapid changes in product models, integrate customer feedback, and adapt to evolving manufacturing requirements. This flexibility is crucial for minimizing overall capital investment and reducing the setup time for production lines when introducing new models. In this paper, a CAPP system for prismatic parts has been developed employing machining features derived from an automatic feature recognition system. The suggested methodology entails the creation of several algorithms for the automatic selection of tools, machines, and precedence constraints. It assists current Computer-aided process planning systems in producing optimal process plans, and the choice of suitable machine and tool can generate extended strategies for optimal production. This paper also presents the development of an optimized process plan for a prismatic part with an objective of minimizing manufacturing time as an evaluation criterion using Genetic Algorithm. An illustrative example part featuring diverse machining features is provided to demonstrate the proposed research.