Aiming to make predictions for reaction conditions that are not as well represented by the training data represents a more significant challenge. To simulate these extrapolative-type tasks, all data points are assigned a group number according to the ligand used and data partitioning was restricted so that all datapoints of the same group can be either in the test or the train set. Thus, the task can be considered as an extrapolation into untrained chemical space. For automating the process of model evaluation, LOGO CV was applied. The ligand was chosen as the variable parameter. Then, the dataset is split up into 31 sections (31 ligands)