Energy planning is one of the most important issues affecting the behaviors and policies of different countries at national and international levels. Concerns over the depletion of non-renewable energy sources and the pollution caused by their consumption have led most countries to focus on renewable energy sources. In this regard, governments are trying to develop policies for extensive use of their renewable energy sources. The precise formulation of such policies requires the development of quantitative approaches to assess the potential of the country in this field. Because selecting inappropriate approaches for evaluating the energy resources leads to wrong decisions in planning and policy-making for the whole energy sector and can cause irrecoverable damages to the country. Since energy issues are multi-dimensional in their nature, the development and selection of the appropriate decision-making approach among the available methods have become a critical issue in this field. In order to overcome this problem, this study proposed a hybrid approach by combining data envelopment analysis (DEA) and fuzzy best–worst method (FBWM) for the prioritization of renewable energy sources (RESs) in Iran. For this purpose, it considered five technical, economic, environmental, social, and political sustainability dimensions into account. The obtained results indicated that the solar, hydroelectric, wind, biomass, and geothermal energy sources are respectively the most efficient RESs in Iran. Also, a three-stage sensitivity analysis approach has proved the consistency of DEA-FBWM approach over the other decision-making methods. Consequently, the proposed approach can be used as a reliable method in the energy policy-making process.