An attempt has been made in this paper to develop a appropriate model for predicting the output responses of Submerged Arc Welding (SAW) process with the help of neural network technique. Also a mathematical model has been developed to study the effects of input variable (i.e. current, voltage, travel speed) on output responses (i.e. reinforcement height, weld bead width, metal deposition rate). SAW process has been chosen for this application because of the complex set of variables involved in the process as well as its significant application in the manufacturing of critical equipments which have a lot of economic and social implications. Under this study the neural network model is trained according to the actual inputs and outputs. When the training is completed then the desired inputs are given to the model and it gives the estimated output value. And according to this we can also estimate the error between the actual and predicted results. Side by side accurecy of mathematical model has been checked.