Interval-valued hesitant Fermatean fuzzy sets (IVHFFSs) offer a powerful mathematical tool for addressing decision-making problems full of uncertainty and ambiguity. Despite their potential, multi-attribute group decision-making (MAGDM) methods within this context have not been extensively explored. This paper addresses this gap by introducing a consensus-based MAGDM approach for IVHFFSs. First, we propose an interval-valued hesitant Fermatean fuzzy (IVHFF) distance measure without normalization, which does not generate data redundancy. Next, we propose an objective expert weighting method based on hesitancy and consensus level. Furthermore, combined with the proposed distance measure and expert weighting method, we propose an IVHFF consensus model. Since the consensus model directly adjusts the expert evaluation value through the distance matrix, it effectively improves the efficiency of consensus reaching. Finally, based on the proposed consensus model, we propose a novel MAGDM method under IVHFF environment.