The right selection of process parameters is a major problem for the researchers. The sectors' decision-makers must consider a large variety of attributes based on a set of contradicting criteria. Several multi-criteria decision-making (MCDM) techniques are available to enhance the selection of these parameters. This paper examines the use of the TOPSIS, VIKOR, and MOORA methodologies to determine the optimal arrangement of processing parameters in submerged arc welding (SAW). Consideration is given to one case study on optimization. This case study is based on the experimental work conducted by Rao and Kalyankar on the SAW of Cr–Mo–V steel.[1]. Important input process parameters are wire feed, welding current, welding speed, and voltage. The influence of these factors on different responses about weld penetration, bead width, tensile strength, weld reinforcement, and weld hardness is investigated. Comparing the TOPSIS, VIKOR, and MOORA procedures demonstrate that all three techniques have shown similar results and are interchangeable. The Taguchi analysis-based TOPSIS technique is compared to the Jaya algorithm, QO-Jaya algorithm, and teaching learning-based optimization (TLBO).