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Society heavily relies on fossil fuels for energy generation, which poses risks like geopolitical conflicts, environmental degradation, and climate change. Opting for renewable energy sources, such as bioenergy from microorganisms, presents a potential solution to these challenges. Harnessing the energy-producing capabilities of microorganisms enables large-scale renewable energy production, without harming the environment or human activities. Thus, the primary objective of this study was to develop a decision-making method for microbial energy generation, using Mamdani-type fuzzy logic to handle the inherent uncertainties and inaccuracies in this field. A four-level indication structure was created, employing triangular and trapezoidal functions at its endpoints. For fuzzy rule development, five input fuzzy sets and five output fuzzy sets were used when two indicators were involved in the fuzzy machinery, while three input fuzzy sets and five output fuzzy sets were used when three or more indicators were part of the fuzzy machinery. Five scenarios were developed, ranging from 0 to 10 on the following scale: High Criticality (10–8), Tolerable (8–6), Adequate (6–4), Desirable (4–1.5), and Low Criticality (1.5–0). This model is expected to optimize decision-making processes and promote renewable energy alternatives, potentially reducing the dependence on fossil fuels in the future.