We employed a hybrid combination of heuristic optimization and nonlinear machine learning classification methods. Building upon our previous work , this new four-taste predictor was trained and tested using similar ensemble dimensionality reduction and classification techniques. This approach effectively reduced the number of physicochemical features and identified the important ones for predicting the four different tastes. The simplicity of the model reduces the likelihood of overfitting and makes it more user-friendly through a web interface (), expanding the potential audience of users. VirtuousMultiTaste is a machine learning-based web tool that predicts four different tastes and opens the possibility of analysing different compounds and understanding the chemical-physical factors that contribute to the overall taste perception.