 Finding the appropriate weight for each criterion is one of the main points in multi-attribute decision-making, MADM, problems. Shannon's entropy method is one of the various methods for finding weights discussed in the literature. However, in many real-life problems, the data for the decision-making processes cannot be measured precisely and there may be some other types of data, for instance, interval data and fuzzy data. The goal of this paper is the extension of the Shannon entropy method for the imprecise data, especially interval and fuzzy data cases. This article was authored by Reza Falanijad and Fahad Haasian Zeta Latfi.