Analysis of the mechanical properties of existing road pavements is crucial for pavement rehabilitation and management problems. Numerous Studies have focused on developing an efficient method for determining the structural conditions of pavements. Nondestructive testing (NDT) methods can characterize stress-strain behavior of pavement layers at relatively low strain levels. However, the majority of NDT techniques are based on measuring the deflections caused by an applied load to determine the stress-strain behavior. Structural analysis techniques can also calculate deflections using material and loading properties where it is commonly necessary to make an inversion between measured deflections and mechanical properties using a back-calculation tool. Soft computing techniques, i.e. neural networks, fuzzy logic, genetic algorithms, and hybrid systems, have successfully been used to perform efficient and precise back-calculation analyses. This chapter explains the advances in pavement back-calculation methodologies based on soft computing approaches by presenting the concepts behind them and the fundamental advantages of each. An alternative utilization of soft computing techniques for pavement engineering is also presented.