The availability of tailored enzymes is crucial for the implementation of biocatalysis in organic chemistry. Enantioselectivity is one key parameter defining the usefulness of an enzyme and, therefore, the competitiveness of the corresponding industrial process. Hence, identification of enzymes with high enantioselectivity in the desired transformation is important. Currently, this is achieved by screening collections and libraries comprising natural or man-made diversity for the desired trait. Recently, a variety of improved methods have been developed to generate and screen this diversity more efficiently. Here, we present and discuss the most important advances in both library generation and screening. We also evaluate future trends, such as moving from random evolution to more rational.