Carbon dioxide capture and storage is one of the primary mitigation approaches endorsed by current global climate change policies, since it is the largest contributing gas to the greenhouse effect. Recently, deep eutectic solvents (DESs) have been found as promising green solvents for CO₂ capture, particularly in industrial applications. Compared to conventional ionic liquids, for example, DESs display similar solvent properties but they are far cheaper, easier to prepare, and greener. Yet their major drawback is linked to their high viscosity that impedes management not fulfilling industrial demands. Further efforts are thus required to develop new DES solvents that hold together high capacity for CO₂ uptake and low viscosity. In this work, we adopted a desirability-based decision approach to jointly handle these two conflicting properties. We began by setting up Quantitative Structure-Property Relationships (QSPR) models for uncovering the two properties based on a dataset of known binary DESs. Then, desirability functions derived from the individual QSPR models were found and combined into an overall desirability-based criterion that was applied to screen and rank two libraries, one comprising experimentally reported DESs and another one with newly designed DESs. The latter enabled us to propose novel efficient DESs for CO₂ uptake, i.e., with the most suitable trade-offs between CO₂ absorption capacity and viscosity. Finally, but most importantly, this work demonstrates the usefulness of the desirability-based approach for the rational discovery of deep eutectic solvents or other materials to suit particular sustainable applications.