Abstract: The main goal of information fusion is to combine heterogeneous information to obtain an alternative solution for composite comparable mode. A decision-making method of fuzzy information fusion based on multi-criteria (FIFB-MC) is proposed. The basic theoretical concepts in the field of computational intelligence and multi-criteria decision-making are combined in the algorithm. Firstly, the normalized basic mode is used to standardize the attribution function. Secondly, the effective data information function value is selected to be combined into an aggregate function, and then the aggregation function is established. The standard approach to deal with heterogeneous information ultimately leads to a single evaluation model for each candidate alternative. Experimental results show that the fuzzy information fusion algorithm based on multi-criteria can process and represent the inaccuracies and uncertainties involved in the input data, and is more adaptive than the fuzzy rule-based method.