For the multi-attribute decision making problem with attribute weights being unknown and attribute values being hesitant fuzzy sets, this study proposes a multi-attribute decision making method based on prospect theory and rough set, which fully considers the influence of decision makers' psychological risk factors on decision results. Firstly, the positive and negative ideal points are used as reference points to calculate the prospect value function under each attribute and to define a new comprehensive prospect value, and a discernibility matrix is obtained according to the given threshold. Then, according to the discernibility matrix, attribute reduction is performed to determine the attribute weight. Finally, the weighted comprehensive prospect value of each alternative is calculated, and the TOPSIS method is used to rank all the alternatives. An example is given to illustrate the feasibility and effectiveness of the proposed method.