•Neural networks to estimate the refractive index of imidazolium-based ionic liquids.•Purity determination by comparison of estimated and experimental refractive indices.•Only the molecular weights are required as previously known information.•Chemical approach by relating molecular weights and refractive indices.•Successful results obtained with both bibliographical and experimental data. Dialkylimidazolium-based ionic liquids (ILs) are one of the most employed and accessible ILs. These novel chemicals possess unique physicochemical properties which, unfortunately, are greatly altered by impurities. A simple method to evaluate the purity level of ILs is proposed, as a direct relationship exists between refractive index (RI) and purity. Two multilayer perceptrons (MLPs) have been designed to estimate the RI values using the molecular weights (MWs) of the imidazolium-based ILs. The RI is defined as the single output of the created neural network models. These MLPs offered low verification prediction errors (less than 0.48% in both cases), thus leading to useful mathematical tools that are able to more than adequately estimate the RI of imidazolium-based ILs by solely relying on the MWs. Therefore, an extremely manageable mathematical tool that can accurately estimate the RIs of imidazolium-based ILs, and, in the end, their purity, has been created. Additional tests were developed with experimental data regarding two imidazolium-based ILs to evaluate the applicability of the networks, and the results were successful in terms of RI and purity estimation.