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Phytoplankton are important aquatic biota which act as the primary producer in waters. Nutrient enrichment can lead to excessive abundance of phytoplankton or eutrophication that harms other aquatic organisms. Especially freshwater areas are susceptible to anthropogenic activities that produce organic waste discharges. These activities can worsen the nutrient enrichment in the aquatic ecosystem. This study aimed to predict the freshwater phytoplankton biomass by using the Wang-Mendel fuzzy algorithm as the function of nutrient concentration (nitrate, phosphate) and other water quality parameters (temperature, transparency, pH, dissolved oxygen). The data were collected from various sources that cover 10 rivers/lakes/reservoirs located in East Java province, Indonesia. The results showed that the proposed model performed well in predicting actual phytoplankton biomass. A better model was produced by utilizing all water quality parameters as the predictors instead of the eutrophication model that only accommodated nutrient predictors. Moreover, this model also outperformed the prediction resulting from multiple linear regression.