The probabilistic hesitant fuzzy multi-attribute group decision-making (MAGDM) problem, with known attribute weights and unknown expert weights, is studied. First, to overcome the shortcomings of traditional distance measures of probabilistic hesitant fuzzy element (PHFE), new distance measures are proposed, whose effectiveness and validity are mathematically proved; Second, under the premise that attribute weight vector is known, the first probabilistic hesitation fuzzy information aggregation, from the perspective of a single expert, is realized through weighted arithmetic average (WAA); Then, based on the criteria of maximizing score deviation (MSD), a model to solve expert weight is constructed and an analytical solution is derived; Finally, based on TODIM, a probabilistic hesitant fuzzy multi-attribute group decision-making method is developed to realize second information aggregation, which is further applied to the evaluation and selection of combat plans