The steel industry is a cornerstone of global economies, but also one of the most energy-intensive sectors, contributing significantly to CO₂ emissions. This issue is exacerbated in developing countries, where rapid industrial growth, outdated technologies, and resource limitations drive higher energy consumption. This study identifies and ranks energy-consumption-reduction technologies for the steel industry in developing economies, focusing on their applicability and potential for significant energy savings. The research integrates the Fuzzy Delphi Method (FDM) and Interval Type-2 Fuzzy Best-Worst Method (IT2F-BWM) to screen and prioritize technologies under conditions of uncertainty. Seven key technologies were validated by an expert panel, including waste heat recovery systems, hydrogen injection, and improvements to continuous casting. The IT2F-BWM model effectively handles expert judgment imprecision and provides a robust ranking of technologies based on criteria such as energy efficiency, economic feasibility, and environmental impact. The findings reveal that technologies such as waste heat recovery and hydrogen injection offer the most significant potential for energy savings (10-50%) and contribute to global decarbonization goals. This study provides policymakers and industry leaders with a practical decision-making tool, offering a pathway to sustainable energy practices tailored to the unique challenges of developing economies. Future research should explore dynamic modeling and cross-country comparisons further to refine energy efficiency strategies for the steel industry.