The mechanical property of thermoplastic polyurethane (TPU) components produced by 3D printing is experimentally investigated in this work using ANFIS for parametric optimization. The objective of this work is to enhance the tensile strength, elasticity, and mechanical behavior of 3D-printed TPU components by identifying and optimizing three important printing parameters of 3D printers: layer thickness, print temperature, infill pattern, and infill density. The mechanical property is optimized by use of the Taguchi Design of experiment table. Tensile strength is greatest at 215 °C printing temperature, 40% infill density, 0.2 mm layer thickness, and 20.77 MPa in LINES infill pattern. At 205 °C, 60% infill density, 0.2 mm layer thickness, and 1.249 MPa in CROSS infill pattern, the highest compressive strength is achieved. ANFIS model was then created to predict mechanical characteristics based on the input parameters after rigorous experimental design. ANFIS model significantly improves the characteristics of TPU parts which successfully determines ideal printing conditions. This work opens the door for new applications especially in footwear industries demonstrating the possibility of combining ANFIS with additive manufacturing techniques to obtain better material property at desired working needs.