The study was conducted in Lake Baringo and determined quantitative relationships between water level changes, water quality, and fishery production for informed lake basin management. Long-term (2008 to 2020) data on water level, water quality, and fisheries yields from Lake Baringo were analyzed using a combination of statistical methods. Linear and waveform regression analyses described patterns of lake level fluctuations over time while, Pearson’s correlation determined the concordance of lake level changes with water quality parameters, landings, and condition of fish species. PCA results grouped the study period into different years based on annual water quality variable levels. LOWESS analysis showed the decline of annual lake level amplitude over time with peak values in 1964 (8.6 m) and 2008 (9.4 m). The waveform regression significantly modeled lake level fluctuations as indexed by annual deviations from the long-term average (DLTM) and showed a 20-year oscillation between peak water levels in the lake. There were significant positive correlations of Water Level Fluctuations (WLFs) with water quality variables and water quality index (WQI) in Lake Baringo. Linear regression analyses showed a significant concordance (p < 0.05) between the annual fishery yield and the rising WLFs (r = 0.66). Overall, the results demonstrate that WLFs of Lake Baringo are a driver of fish species biomass and physico-chemical properties of the lake. We recommend the integration of fisheries yields, water quality assessment, and WLFs modeling at different temporal scales in the management of Afrotropical lake ecosystems