Abstract: In this paper, a knowledge-based artificial neural network is used to model the symmetrical unilateral fin-lines. Utilizing prior knowledge for reducing complexity of input-output relationships that the Artificial Neural Network (ANN) must learn, it allows an accurate ANN model to be developed with less training data which is very advantageous when training data is expensive/time Consuming to obtain, such as with EM simulation. The neural network is electromagnetically developed with a set of training data that are produced by the finite elemont method (FDTD). which is robust both from the angle of time of computation and accuracy.