Abstract: The invention relates to a method for predicting yield performance of a crop plant, comprising the steps of receiving metabolite measurements of the crop plant; determining new metabolite features by combining the received metabolite measurements, wherein at least one new metabolite feature is based on a classified average; providing the new metabolite features to a trained machine learning model; and determining yield performance of the crop plant using the provided model. It also relates to a method for training a machine learning model for predicting yield performance of a crop plant; a control unit configured to execute the method for predicting yield performance; to a plant breeding method and a farming method that apply said method; and the use of new metabolite features as determined in said method for prediction of yield performance.