Uncertainty was introduced to chemical descriptors of 16 publicly available data. sets to various degrees and in various-ways order to investigate the effect on the predictive performance Of the State of-the-art method decision tree ensembles. A number of strategies to handle uncertainty in:decision tree ensembles were evaluated. The main conclusion of the Study. is that uncertainty to a large extent may be introduced in chemical descriptors without. impairing the predictive performance of ensembles and without the predictive performance being significantly reduced from a practical point of view. The investigation. further showed that even When distributions of uncertain values were provided, the ensembles method could generate equally effective models from single-point samples from these distributions. Hence, there seems to be no advantage in using more., elaborate Methods for handling uncertainty in chemical descriptors when using decision tree ensembles as a modeling method for the considered types of introduced uncertainty.