Eutrophication poses a substantial environmental problem due to the formation of toxic cyanobacteria in freshwater bodies. These blooms, known as Cyano-HABs (Cyanobacterial Harmful Algal Blooms), are brought on by favorable conditions such as high nutrient concentrations, high temperatures, and the alteration of aquatic ecosystems. To address these phenomena, specific models have been developed using the PLS-PM (Partial Least Square Path Modeling) methodology to assess the potential occurrence of eutrophication events in the A Baxe reservoir (Galicia, NW Spain). Specifically, the effectiveness of the developed models has been evaluated and future scenarios have been proposed to analyze their predictive efficiency in order to improve future decision making. For the construction of the models, the interdependence between eutrophication indexes (Enhanced Vegetation Index [EVI], Normalized Difference Vegetation Index [NDVI], and Floating Algae Index [FAI]), weather conditions (temperature, precipitation and solar radiation), reservoir flow (occupation), water physicochemical data (alkalinity, water temperature, and Water Quality Index [WQI]), and eutrophication parameters (Trophic State Index and cyanobacteria) have been studied. Climatic factors influence the availability of nutrients and the growth of cyanobacteria. Likewise, water physicochemical parameters, such as those included in the WQI, like nitrogen and phosphorus, as well as water temperature, are determinants for the growth and proliferation of these bacteria. In addition, NDVI, EVI, and FAI indices are used to detect the presence and density of cyanobacteria by observing changes in aquatic vegetation and the appearance of floating algae. Model 1 focuses on weather variables (temperature and precipitation), while model 2 considers the FAI index. The PLS-PM analysis yields significant results in both models, showing that 67.4% (R2 = 0,674) of Cyano-HABs episodes can be predicted by the variables examined in model 1 and 74.6% (R2 = 0,746) by those in model 2. The notable influence of temperature (W = 0.999) in model 1, where warmer conditions promote the proliferation of cyanobacteria, and of the FAI (W = 0.326) in model 2, being a specific indicator of the presence of floating algae, also stand out. The use of Sentinel-2 images to calculate EVI, FAI, and NDVI indexes, together with the analysis of weather conditions and physicochemical parameters, has enabled exceptional spatial and temporal resolution to be obtained. The incorporation of these images highlights the ability to detect specific pigments associated with these cyanobacteria, despite the need for calibration and validation with field measurements. The models are presented as tools of vital importance for water management, as they facilitate the formulation of preventive and corrective strategies that ensure water security in watersheds. In addition to their practical usefulness, the models strengthen decision-making and help to improve governance in water resources management. This can be achieved by raising public awareness of the importance of conserving water resources, controlling agricultural discharges, as well as promoting the role of riparian vegetation.