Machining high-temperature alloys like Nimonic PE16 requires precise control of parameters to achieve optimal results, reduce tool wear, and improve surface finish. The first goal is to accurately perform a machinability study on the material Nimonic PE16 to create a dataset for analysis and generate machining trends. Secondly, this study aims to create a predictive model to accurately determine the best cutting speeds and feed rates based on critical outputs such as cutting forces and surface roughness. Next, the microstructure of the material under various heat treatments will be explored to optimize mechanical properties. Lastly, an accurate Finite Element Analysis model was created to simulate the turning process of Nimonic PE16. This framework of models and design of experiments provides a data-driven approach to optimizing machining processes for PE16, enhancing efficiency, productivity, and quality in nuclear and other high-performance applications.