Infrastructure needs planning requires careful consideration of the availability and needs of raw materials, such as fly ash, which is often used in various construction projects. One of the main challenges in this planning is the uncertainty in predicting the supply and demand of fly ash. To overcome this problem, this study applies the Fuzzy Sugeno method, which is an approach in Fuzzy logic, to analyze fly ash stocks and plan infrastructure needs more effectively. This method allows processing uncertain and subjective data, such as estimates of fly ash stock and demand that can vary over time. Using the Fuzzy Sugeno model, calculations are carried out to determine the optimal stock level and predict long-term fly ash needs. The results of this study are expected to provide a more accurate picture of fly ash needs planning and assist related parties in making more efficient decisions in infrastructure planning. The results of the process carried out from January 2023 to December 2023 obtained a mape value of 30%, this value is included in the reasonable category.