Fused Deposition Modeling (FDM) is a widely recognized additive manufacturing method that is highly regarded for its ability to create complex structures using thermoplastic materials. Thermoplastic Polyurethane (TPU) is a highly versatile material known for its flexibility and durability. TPU has several applications, including automobile instrument panels, caster wheels, power tools, sports goods, medical equipment, drive belts, footwear, inflatable rafts, fire hoses, buffer weight tips, and a wide range of extruded film, sheet, and profile applications.. The primary objective of this study is to enhance the FDM parameters for TPU material and construct regression models that can accurately forecast printing performance. The study involved conducting experimental trials to examine the impact of key FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical responses, including dimensional accuracy, surface quality, and mechanical properties. The utilization of design of experiments (DOE) methodology enabled a methodical exploration of parameters. Statistical techniques were employed to develop regression models that establish relationships between process parameters and performance indicators. These models offer a prognostic instrument for optimizing FDM parameters and attaining desired printing results. The results demonstrated the effectiveness of the regression models in accurately forecasting the printing performance for TPU material. The models provide valuable insights into the optimal parameter configurations for maximizing printing efficiency, quality, and mechanical robustness. This study enhances the comprehension of Fused Deposition Modeling (FDM) for Thermoplastic Polyurethane (TPU) material and provides useful techniques for optimizing the manufacturing process. Manufacturers can improve printing productivity and quality by utilizing regression models, thereby promoting the wider use of FDM technology in industries that need flexible and durable components.