The applicability of probabilistic ideas to processes involving particles is first presented and followed by a general definition of a Markov chain which is illustrated by a simple example. The stochastic nature of the concept of grade efficiency in separation processes is demonstrated by assuming a particle of size x to be the system and the grade efficiency function to be a transition probability. This is used to calculate the overall grade efficiency for various classifier networks showing the evolution of the probability of presence of a particle at each point of the circuit as a function of the number of steps. Finally, performing the calculation with indefinite number of classifiers and taking into account dead flux, we emphasize the possibility of modelling complex particle flow in hydrocyclone.