<p>The three-way decision-making method in hesitant fuzzy environments is widely recognized as a powerful tool for addressing uncertainties and ambiguities in the decision-making process. Moreover, prospect theory objectively depicts the effect of decision-makers’ psychological behavior on the decision-making process. Therefore, this article intends to establish a novel multi-attribute three-way decision-making method in a hesitant fuzzy environment by incorporating prospect theory to account for decision-makers’ irrational behaviors. Specifically, to overcome the limitations of existing distance formulas for hesitant fuzzy elements, we introduce a novel formula for computing the distance between hesitant fuzzy elements at first. On this basis, a novel method for computing the conditional probability in hesitant fuzzy environments is proposed. Concurrently, a relative loss function is developed for each scheme by integrating the hesitant fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method with prospect theory, which is utilized to address real-life multi-attribute decision-making problems. Finally, through case and comparative analysis, we demonstrate scientific validity and superior performance of the proposed method, and prove the reliability and robustness of the proposed method through parametric sensitivity analysis. The successful implementation of these methods has fully demonstrated the tremendous potential and advantages of artificial intelligence technology in dealing with complex decision-making problems.</p>