This paper presents a methodology of mapping the bead geometry, deposited on a fillet like joint, as a function of the input parameters of the synergic pulsed gas metal arc welding process and the welding position, to allow the planning of repairing hydroelectric turbine runner blades by means of robotic welding. The challenges of automating the repair process; further, to choosing the best welding parameters, include the definition of the path that the robot must follow during the metal deposition, such that it is able to fill completely the damaged blade cavity, by means of producing overlapped layers from several individual weld beads. Thus, this research focused on developing statistical prediction models that could map the geometric variations of the weld bead section as function of the input parameters (wire feed speed, welding speed and bead face rotation angle). For this purpose, the bead section was approximated by a parallelogram whose height, width and inclination angle were considered as dependent variables. Several welding trials were carried out according to a central composite experimental design and three multiple regression models were obtained. Here, the physics is used to interpret the influence of the input parameters on the output results.