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Forecasting the volume of foreign trade is important to policy formulation for local governments. This study proposes a machine-learning algorithm as a forecasting tool that is based on Rough sets and Shannon entropy. This study uses historical data from a large municipal to examine the proposed forecasting tool. The results suggest that this tool can be useful in specific trade decisions with unique characteristics and requirements.