Lime stabilization has been used as an improvement technique in the soft ground for many years. Pavements with lime-stabilized subgrades result in reduced deflections and improved critical pavement responsnses under applied wheel loading. ILLI-PAVE, a nonlinear finite element program for advanced pavement analysis, was utilized in this study to model pavements on lime-stabilized soils and show benefits of lime stabilization. A wide range of material model parameters and pavement geometrics was studied to obtain corresponding deflections and critical pavement responses. The results were used to create a database for developing artificial neural network (ANN) models and capturing the nonlinear relationship by means of the back propagation algorithm. The developed ANN models worked as highly effective and robust ILLI-PAVE surrogate solutions to investigate the effects of lime stabilization on deflection profiles and critical responses. Significant differences were found between responses of full depth pavements on unmodified subgrade and lime-stabilized subgrade.