AbstractHesitant fuzzy sets (HFSs), as an extension of fuzzy sets, consider the degrees of membership by a set of possible values rather than a single one. For further applications of HFSs to decision making, we develop a concept of hesitant fuzzy preference relations (HFPRs) as a tool to collect and present decision makers’ (DMs) preferences. Due to the importance of consistency measure for HFPRs to ensure that DMs are being neither random nor illogical, we develop a regression method to transform HFPRs to fuzzy preference relations (FPRs) with the highest consistency level. Some examples are given for illustration.