The paper contributes to the Sustainable Development Goals (SDGs) targeting Life Below Water by introducing user-friendly modeling approaches. It delves into the impact of abiotic factors on the first two trophic levels within the marine ecosystem, both naturally and due to human influence. Specifically, the study examines the connections between environmental parameters (e.g., temperature, salinity, nutrients) and plankton along the Romanian Black Sea coast during the warm season over a decade. The research develops models to forecast zooplankton proliferation using machine learning (ML) algorithms and gathered data. Water temperature significantly affects copepods and “other groups” of zooplankton densities during the warm season. Conversely, no discernible impact is observed on dinoflagellate Noctiluca scintillans blooms. Salinity fluctuations notably influence typical phytoplankton proliferation, with phosphate concentrations primarily driving widespread blooms. The study explores two scenarios for forecasting zooplankton growth: Business as Usual, predicting modest increases in temperature, salinity, and constant nutrient levels, and the Mild scenario, projecting substantial temperature and salinity increases alongside significant nutrient decrease by 2042. The findings underscore high densities of Noctiluca scintillans under both scenarios, particularly pronounced in the second scenario, surpassing the first by around 70%. These findings, indicative of a eutrophic ecosystem, underscore the potential implications of altered abiotic factors on ecosystem health, aligning with SDGs focused on Life Below Water.