To improve the currently available models with respect to the accuracy of the model and the suitability for a wide range of chemical substance classes, we collected additional key aspects that we expected to improve the solubility prediction. The main changes included: (1) the application of traditional machine learning algorithms like XGBoost and Random Forest, along with neural networks and (hybrid) message-passing neural networks from graph neural networks.