Forging is one of the traditional bulk metal forming processes used extensively in the automotive industry. Forging has a distinct advantage versus other metal manufacturing processes in terms of strength, grain orientation, reliability, near net shape with lower material utilization, and machining requirements leading to cost effectiveness, etc. Today, the automotive industry is going through the critical phase of reducing component costs through material reduction and optimized tool consumption. With this challenge, process modeling is gaining more momentum in the industry to optimize blank size and improve the tool life with required part quality, while also evaluating press tonnage requirements for effective equipment usage. It also enables integrated process modeling by understanding the microstructure, residual stress/deformation built into the manufactured part, and integrating with material property changes for subsequent part performance prediction. A current case study details the approach to simulate a multi-stage hot forging process. In addition to deformation process modeling, the case study also focusses on billet size and process parameters to predict and obtain desired material flow and avoids filling defects with minimum material waste on forging and machining. Established predictive models through design of experiments can be utilized to control part quality and select forging equipment as per estimated tonnage required to forge a component.