Catalytic converters are indispensable components in the automotive industry, tasked with thecrucial mission of curbing harmful emissions and enhancing air quality. This study conductsan in-depth exploration of catalytic converter design, employing cutting-edge computational methodologies, including SOLIDWORKS and ANSYS FLUENT. The primary objective is tocomprehensively assess fluid dynamics within both conventional and innovative catalytic converter configurations, with a particular focus on crucial parameters such as velocity distribution, dynamic pressure, and turbulent intensity contours. The outcomes of this rigorous analysis reveal compelling insights. The avant-garde catalytic converter design showcases aplethora of advantages over its conventional counterparts, manifesting in a uniform velocitydistribution, diminished turbulence, and a substantially reduced backpressure profile. Theseinrightful findings highlight the enormous potential of ground-breaking catalytic converter designs to revolutionize exhaust system efficiency and make considerable progress in reducing vehicle missions and their effects on the environment. This research not only underscores the criticality of optimizing catalytic converter performance but also emphasizes the pivotal role of state-of-the-art computational tools in devising emissions control strategies. By bridging the gap between theoretical scrutiny and real-worldapplications, this study makes an indispensable contribution to the advancement of emissionscontrol and catalytic converter design, with far-reaching implications for the global pursuit ofcleanertransportation. Data envelopment analysis a multi-response linear programming optimization tool was employed to assess the output and emissions of DI diesel engines using waste plastic oil mixtures.