3D printing is an innovative technology used for producing functional prototypes and visualizing complex physical designs. Different 3D printing methods have been developed to cope with wide variety of mechanical components and materials. These techniques also speed up the mass manufacturing of complex components by quickly producing working prototypes. The performance of the 3D printing process can be assessed by the achieved outputs such as the mechanical qualities of the produced porotype, printing mass, and printing duration. Like any manufacturing process, how a process performs basically depends on the preference of the decision maker; whether all outputs are important or only a set of these outputs. Determining the desired performance is attained by the proper adjustment of process parameters. Selecting the optimal set of printing parameters, canE therefore, be thought of as multi-criteria decision-making (MCDM) problem since conflicting performance metrics are involved in the decision process. Substantial work has been made primarily on choosing printing machines and studying the effects of printing parameters, but with little focus on deciding parameters settings suitable for achieving the desired printing performance. For this purpose, a preference selection index (PSI)-MCDM model is proposed in this paper. The model is demonstrated using a ZORTRAX- M300 plus plastic 3D-printer as a case study. Multiple scenarios with different sets of decision criteria are presented to reflect users’ predilections. The outcomes show the model's capability to rank parameter combinations in a methodical manner.