This article demonstrates the efficiency of the application of the theory of Markov chains as a tool to model and simulate continuous ponder miring to aid in better design of such equipment. Markov chair models allow calculating practically all parameters of the process necessary for its characterization, and in particular those related to particle residence tune distribution (RTD). Some numerical examples from tire model, which are important for better understanding the process, are also included. It is shown that the main factor defining the efficiency of continuous mixing, through the variance reduction ratio (VRR), is the ratio of the mean residence time and the period of inflows fluctuation. rather than the variance of the RTD. Also, the influence of the dimensions of the mixer outlet on the meaty residence time, and in turn on the VRR, is examined as another way of improving the design.