The dataset include hydroclimate and ambient environmental as the input data and Cyanobacterial HABs Index (CI) calculated from satellite imageries as the output data altogether used to train and validate three data-driven (machine learning) models and their Ensemble Average (AE) to predict HABs cell count in southwest Lake Erie. The data also include HABs volumetric and areal concentrations obtained from literature and used in conjunction with the CI calculated from satellite data to develop statistical regression models for use to convert model predicted CI values (cell counts) to volumetric/areal concentrations of HABs.