The world energy crisis and environmental damage require that sustainable fuel sources be embraced. Fossil fuels are depleted very fast, and the more people rely on them, the higher the chances of causing climatic change, thus necessitating a shift to renewable sources of energy. Bioenergy has become one of the solutions in this respect since it produces clean and renewable fuels using organic materials. The bioenergy sector could reduce greenhouse gas emissions and provide a boost to the circular economy by leveraging advanced technologies. However, not all these bioenergy technologies are equally efficient or scalable. Finding the best bioenergy technologies for producing sustainable fuels is important in today’s world. This study focuses on prioritizing advanced bioenergy methods that transform resources such as biomass, algae, and organic waste into clean energy. This study uses a hesitant bipolar fuzzy sets (HBFSs) multi-criteria decision-making (MCDM) approach based on Hamacher prioritized operators for the evaluation and ranking of advanced bioenergy technologies. This methodology effectively addresses the uncertainty and conflicting criteria in decision-making.