<p>In the twenty-first century, the widespread use of vehicles presents a major challenge for users in selecting alternative fuel vehicles. The foremost task is to choose the best fuel technology for land transportation to create a sustainable system under multiple criteria. However, obtaining precise data is not always feasible in real-life scenarios, so, uncertain data, specifically Pythagorean fuzzy data, is considered. multi-criteria decision-making (MCDM) is essential for addressing complex decision-making problems. This study introduces the Pythagorean fuzzy ordered weighted averaging (PFOWA) aggregation operator to tackle MCDM problems. The research explores the application of MCDM for selecting alternative fuels in sustainable urban transportation, where the PFOWA operator, combined with an appropriate score function, helps assess the importance and ranking of criteria for more effective decision-making. Using this aggregation approach, suitable alternative fuels for urban transportation were identified and the study’s final results presented. This paper explores the selection of alternative fuels for sustainable urban transportation through the application of the PFOWA aggregation operator. The fuels considered are electric buses with exchangeable batteries (EEB), methanol (MET), compressed natural gas (CNG), hybrid electric vehicles with CNG engines (HEC), and liquid petroleum gas (LPG). After calculations, the results show the preferences of fuel options as LPG—the Best preferred choice and MET—the Least preferred choice. The results may vary in different parts of the globe, as differences in climate, fuel availability, and country-specific factors can significantly affect the end results.</p>