ML flowchart of our framework. It begins with the acquisition of the publicly available SC4K and COSMOS2020 catalogs. The acquired data are then preprocessed, which involves sampling, integrating, and extracting the samples to be used by the ML models. This is followed by extraction of fluxes and magnitudes as features together with the creation of colors using the latter. The training phase involves the optimization of hyperparameters using a grid search for each algorithm: LightGBM, XGBoost, and CatBoost. Finally, the final target label is obtained by combining all the individual predictions into a single prediction using soft voting.