One of the ways used to seal and robust rock foundations is injection slurries into joints and cracks. Groutability is very difficult to predict and for this purpose engineers usually use trial and error method that will increase the cost of projects. In this study, a new method for modeling the grouting jointed rock mass is designed using an explicit algorithm and basis o grouting pressure forehead in discrete fractured network (DFN) and then in a Computer software has been developed to groutiut2d. Groutiut2d including getting input parameters, calculation and graphical output which shows grout propagation surface and its area. In this study mentioned software to conduct sensitivity analysis were tested with Monte Carlo method in a total of 400 samples And its results was moved to a artificial neural network (ANN). ANN results were presented in form of graphs. According to these results, in overall, increasing pressure, time and density and viscosity reduction increase the surface area of grout propagation in jointed rock mass
