Professionals in industries are making progress in creating predictive techniques for evaluating critical characteristics and reactions of engineered materials. The objective of this investigation is to determine the optimal settings for a 3D printer made of acrylonitrile butadiene styrene (ABS) in terms of its conflicting responses (flexural strength (FS), tensile strength (TS), average surface roughness (Ra), print time (T), and energy consumption (E)). Layer thickness (LT), printing speed (PS), and infill density (ID) are all quantifiable characteristics that were chosen. For the experimental methods of the prediction models, twenty samples were created using a full central composite design (CCD). The models were verified by proving that the experimental results were consistent with the predictions using validation trial tests, and the significance of the performance parameters was confirmed using analysis of variance (ANOVA). The most crucial element in obtaining the desired Ra and T was LT, whereas ID was the most crucial in attaining the desired mechanical characteristics. Numerical multi-objective optimization was used to achieve the following parameters: LT = 0.27 mm, ID = 84 percent, and PS = 51.1 mm/s; FS = 58.01 MPa; TS = 35.8 MPa; lowest Ra = 8.01 m; lowest T = 58 min; and E = 0.21 kwh. Manufacturers and practitioners may profit from using the produced numerically optimized model to forecast the necessary surface quality for different aspects before undertaking trials.