(Abstract) Decision-making model for multidimensional analysis of preference on trapezoid fuzzy number distant expected values are proposed. The group decision-making problem are solved when preference and attribute are given by trapezoid fuzzy number .Its algorithm is as follows: First, define a distortion function between subjective / objective analysis of preference under B-cut set to get weighted vector of the attribute through constructing a criterion-programming model. Second, congregate the weighted normalization fuzzy decision matrices of all the decision-makers under different B-cut sets to form a total weighted normalization fuzzy decision matrix. Finally, get relative closeness S of each alternative adjustment decision and then sort by size to determine the optimal program. (3) are the common solutions to solve fuzzy multi-attribute decision-making problems. Among them TOPSIS method is the most classical. Literature (4) find the program's ideal solution and negative ideal solution based on fuzzy numbers' extreme points and the literature based on maximum and minimum value. For the fuzzy number distance, the literature use the vertex method that is Euclidean distance, the literature uses Hamming distance, and the literature introduces Minkowski distance. For the sorting of fuzzy numbers, the literature introduces a Rs partial order relation, literature propose the expected value TOPSIS method, the literature gets the program's ranking results through congregating ranking vectors under different α -cut sets. Currently there are fewer literatures about the research on incomplete weighted information and the program with preference trapezoid fuzzy number expected value TOPSIS method to solve the group decision-making problems. Herein, we propose a group decision-making model for multidimensional analysis of preference based on trapezoid fuzzy number distance expected values. The algorithm is as follows: First, normalize the trapezoid fuzzy number decision-making matrix, define distortion function between subjective and objective analysis of preferences under B -cut set and get weighted vector of the attribute through constructing a criterion-programming model; then congregate the weighted normalization fuzzy decision-making matrices of all the decision-makers under different B-cut set to form a total weighted normalization fuzzy decision matrix.; and then we get relative closeness Q of each optional program and the fuzzy ideal solutions based on distance expected value TOPSIS method and then sort by size to determine the optimal program. Finally, we show the effectiveness of this group decision-making model through examples.