LGBM model trained on organic solubility dataset comprising 5,081 datapoints performed better than a deep neural network model for unseen solutes. In the case of aqueous solubility, Boobier and coworkers showed the AquaSol model, which is an undirected recursive neural network model, was comparable in performance to an Extra Trees model and a RF model. The models were trained on the data obtained from Open Notebook Science Challenge aqueous solubility dataset and the Reaxys database.