In this study attention was focused on the development of a predictive model for the viscosity of ionic liquids. A large data set of 435 experimental viscosity data points for 293 ionic liquids incorporating 146 cations and 36 anions was applied for the model derivation. A quantitative structure property relationship (QSPR) approach was employed to develop a linear model. In this study the effects of both anions and cations were considered in the derivation of the model. Genetic function approximation is applied for the model's parameter selection (molecular descriptors) and developing a linear QSPR model. Consequently, a simple linear predictive model was obtained with satisfactory results quantified by the following statistical parameters: absolute average deviations (AAD) of the predicted properties from existing experimental values by the GFA linear equation, 8.77%; squared correlation coefficient, 0.8096; and root mean square, 0.232 cP.