In the developing domain of decision-making (DM), uncertainty and ambiguity are among the biggest obstacles. This research paper presents a DM method for hesitant fuzzy soft sets (HFSS). It involves obtaining or constructing HFSS, incorporating adaptive parameters, calculating the euclidean distance between sets, determining the similarity measure, and comparing options based on similarity. It also presents the algorithm used in intuitionistic fuzzy soft sets using similarity measures to HFSS. The step-by-step approach ensures a systematic and logical decision process, incorporating adaptability and distance calculation. The study gives the influence of different distance measures on DM processes, providing a comparative study and the effectiveness of the proposed algorithms with a case study.