For the first time, a unified single approach to the selection of both input and output variables of a stochastic model, i.e. to the problem of identifiability of a system with structural identification, is presented. This approach is based on a Rényi-consistent (all terms will be explained in the text) dependence measure of random variables and random vectors and does not assume any other a priori assumptions about the system itself or restrictive assumptions about the characteristics of the probability distributions of the components included in the system.