The real exchange rate of national currency is known to be one of the most important macroeconomic indicators. In this paper, we explore the opportunities of the Monte Carlo simulation technique combined with the polynomial residuals model for a medium-term forecasting the index of the real effective exchange rate for the ruble. The idea of the proposed approach is based on the successive (variable) differences method, designed for smoothing time series characterized by trend component and irregular component. The approach is illustrated numerically with the simulation-based forecast for the ruble real effective exchange rate, the values of the index in September-December 2017 being used to assess the forecast quality. The parameters in the corresponding polynomial residues models were calculated using the Nelder–Mead algorithm. The results of simulations at different "estimate depth" values and MAPE and RSME values indicate that the proposed approach allows constructing a relatively accurate medium-term forecast for the ruble effective exchange rate.