The application of expert systems has emerged as a cost efficient tool in civil engineering over the past decades. Use of these tools for decision making in land use will be outlined in this paper. In this study, soil-structure interaction (SSI) is discussed by using expert systems, namely, neural network (NN) approaches. This method provides a new point of view for evaluations of SSI and land use. Data from 58 local sites in California, namely, earthquake, structure, and soil property data, are used. In the expert system approach, two NN architectures are used: the back propagation NN architecture and the general regression NN (GRNN) architecture. There are 21 parameters considered as input and 4 output parameters. The four output parameters chosen are soil-to-structure rigidity ratio, period lengthening, foundation damping, and whether SSI effects can be neglected or not. The results show that the GRNN approaches are more useful and powerful for evaluation of SSI and land use.