A multi-attribute decision making method based on signed distance and cross entropy is proposed for multi-attribute decision making problems in which the attribute weights are completely unknown under the probabilistic hesitant fuzzy environment. Firstly, the three kinds hesitation degree of probability hesitant fuzzy elements used to measure the degree of hesitancy of decision makers is proposed: Numerical hesitation degree, information incomplete degree and total hesitation degree. The probability hesitant fuzzy signed distance is proposed based on three hesitation degrees. Then, in order to avoid artificially adding elements, the adjusted probabilistic hesitant fuzzy element is defined, it combines with the incomplete degree of information to propose the cross entropy of the probabilistic hesitant fuzzy element. Finally, the multi-attribute decision model is constructed based on the signed distance and cross entropy of the probabilistic hesitant fuzzy element, and the effectiveness and rationality of the model are illustrated by an example.