<p>By using probabilistic hesitant Pythagorean fuzzy sets, people can characterize complex fuzzy information and make reasonable judgments or effective decisions through information processing. In this process, the comparison and ranking of fuzzy information is usually a key concern. The main purpose of this work is to explore ranking methods of fuzzy information and multi-criteria decision-making (MCDM) methods in complex probabilistic hesitant Pythagorean fuzzy environments. Firstly, definitions of score, accuracy, and variances are given for probabilistic hesitant Pythagorean fuzzy elements, and a new ranking method based on these indicators is proposed. Secondly, definitions of score, accuracy, and variances are presented for probabilistic hesitant Pythagorean fuzzy vectors, and a ranking method is developed accordingly. In addition, an MCDM method is proposed in probabilistic hesitant Pythagorean fuzzy environments. Finally, the effectiveness of the proposed ranking methods and the MCDM method are verified through application examples and comparative analysis. It is shown that: (1) the proposed ranking methods can effectively solve the problems of inability of achieving complete ranking or unreasonable ranking results in existing methods; (2) the developed MCDM method has the advantages of simple decision-making process and reasonable and effective decision-making results.</p>