This thesis brings forward an automatic inductor synthesis tool at microwave band according to the user’s specification by using back-propagation neural networks (BPNNs). Inductor is one of critical component that dominate the overall performance of RF devices in RF design, and inductor design is often one of most difficult and time consuming process. In order to solve the above problem, we propose the method of automatic inductor synthesis using neural networks. The results of EM simulation or measurement of inductors served as a basis for neural network training with suitable training procedure. The neural networks then can predict inductance and Q-value for a given inductor layout. These neural models can speed up the inductor design by automatically generating the layout of planar spiral inductors according to the user’s specification.