The horizontal fillet welding is prevalently used in heavy and ship building industries to fabricate the large scale structures. A deep understanding of the horizontal fillet welding process is restricted, because the phenomena occurring in welding are very complex and highly non-linear characteristics. To achieve the satisfactory weld bead geometry in robot welding system, the seam tracking algorithm should be reliable. The number of seam tracker was developed for arc welding automation by now. Among these seam tracker, the arc sensor is prevalently used in industrial robot welding system because of its low cost and flexibility. However, the accuracy of arc sensor would be decreased due to the electrical noise and metal transfer. In this study, the signal processing algorithm based on the neural network was implemented to enhance the reliability of measured welding current signals. Moreover, the seam tracking algorithm in conjunction with the signal processing algorithm was implemented to trace the center of weld line. It was revealed that the neural network could be effectively used to predict the welding current signal at the end of weaving.