With technology development, there is a growing need for an accurate simulation tools, allowing the best possible representation of the reality. Developed model found not only application in prototyping process but can provide significant knowledge into the artificial intelligent model extending their comprehension. Computational performance and accuracy of the numerical model, dedicated for granular flows are mostly a function of mathematical model that track the mutual interaction between particles. Currently the kinetic theory of granular flow or soft- and hard-sphere collision models are used for modeling particle interactions. Each of them suffers from some imperfection that often limit the problem sizes. The purpose of this work is building new mathematical approach, not only fast, but also accurate regarding predicting collisions and determining particle trajectories by application of machine learning technique.