The development of renewable energy is not only a pressing solution to address climate change but also a driving force for sustainable economic growth. Numerous technologies exist for sustainable energy development, each characterized by various criteria, making performance evaluation challenging. This complexity renders the selection of the optimal option a multi-criteria decision-making (MCDM) problem. This paper presents a study on the application of MCDM techniques to select the best option among eight sustainable energy development alternatives: hydropower, geothermal energy, biomass energy, wind energy, solar energy, concentrated solar power, coal-fired power plants, and oil-fired power plants. The Probability method was employed as the MCDM approach in this research. The ranking results of sustainable energy development alternatives using the Probability method were compared with those obtained using other methods, including CURLI, TOPSIS, PIV, and RAM. The results demonstrated that the sustainable energy development alternative identified as the best using the Probability method was consistent with the results of other MCDM methods. Moreover, the Probability method exhibited a high degree of stability in the ranking of alternatives under various weight scenarios. Consequently, geothermal energy was determined as the most suitable sustainable energy development option among the eight alternatives examined.