Identifying criteria and determining their importance toward achieving a goal is a challenging yet crucial activity in the multi-criteria decision-making (MCDM) process. In practice, it is common for different decision-makers (DMs) to have varying perspectives on identifying the best and worst criteria. However, the existing literature lacks approaches that effectively address this issue. This gap underscores the need for more robust methodologies. To address this, our study proposes a novel fuzzy reference best-worst model, which integrates the benefits of the best-worst method (BWM) and triangular fuzzy theory, thereby addressing the gap in current theory. By introducing the reference best and worst points into the fuzzy best-worst method (FBWM), the model assists decision-makers in weighting criteria more efficiently and effectively. The framework presented in this study makes a valuable contribution to the field of MCDM. It offers a robust and efficient tool for decision-makers to assess and prioritize criteria, leading to more informed and effective decision-making processes.