The design of chemical reactions encompasses various aspects, from the choice of the employed catalyst to the selection of ideal reaction conditions. While traditionally, all of this has been performed by intuition and rational design, the last years have witnessed a surge in data-driven approaches to improve the design of reactions, e.g., by inferring mechanistic features through statistical modelling, the generation of catalyst structures with increased catalytic activity, or optimising the reaction conditions to maximise the yield or selectivity. In contrast to the direct approach as seen in many examples discussed so far, where starting from a molecular structure and a set of conditions, the reaction outcome is predicted, optimising the design of a reaction can be framed as an inverse design approach . Given a target, e.g., fast conversion or high selectivity, the task is to find a catalyst structure or a set of conditions to satisfy the requirement. The following chapter will give an overview of recent advances in the design of organocatalytic reactions.