This Chapter discusses how to determine the residence time of breakage of the materials in the ball mill in order to forecast any state of grinding of the ball mill. Using Genetic Algorithm the desired state of grinding of the ball mill is predicted based on its two previous consecutive states and after running the ball mill up to that predicted state, it is stopped automatically. At that desired state, the mill comes to an end, and the targeted particle size distribution (psd) of the material is collected. Discussion follows how the optimum parameters of grinding are decided to stop the mill by designing a fitness function, which minimizes material wastage. Next the discussion is on the procedure to correlate the particle size distribution at different states of grinding and determining the residual time to stop the mill when the desired breakage particles are acquired, thus minimizing the loss of materials. The particle size distribution of the materials at different states of grinding are obtained by applying Gaussian Mixture Model (GMM) and clustered using fuzzy c-means (FCM) algorithm where number of groups are equal to the predetermined states of the ball mill. When the mill stops, the psd of the breakage material corresponding to a particular state must belong to the respective cluster, verifying the experimental result.