This chapter will extend the discussion about linear analysis to nonlinear analysis using neural networks. There are several methods suitable for nonlinear analysis, including multilayer perceptron (MLP) networks, radial basis function (RBF) networks, support vector machines (SVMs), generalized model for data handling (GMDH), also called polynomial nets, generalized regression neural network (GRNN) and generalized neural network (GNN). Most of these networks have several processing layers that give them nonlinear modeling capability.