The chemical industry makes extensive use of solvents in both reaction and separation processes. The large number of existing and potentially new solvents calls for systematic methods for optimal solvent selection and design to reduce experimental efforts and accelerate process development in the early phase. There have been numerous contributions made towards the optimal selection and design of solvents as mass separating agents for various separation processes. In comparison, despite of the strong impact of solvents on chemical reactions by changing the reaction rate and/or shifting the chemical equilibrium, limited work on reaction solvent selection has been reported. Moreover, there is still a lack of insightful perspective article on model-based reaction solvent selection/design. In this work, we address this shortcoming by summarizing the state-of-the-art studies on reaction solvent selection/design using various computational methods, with a focus on group contribution and conductor-like screening model (COSMO)-based modeling approaches. Solvent selections for reactions integrated with up- and/or downstream process design, including the impact of catalyst and a group contribution extension to the COSMO models, are highlighted as potential future directions.