The invention discloses a mail classification method combining user relationships with the Bayers theory. According to the method, through extracting user relationships contained in mails to construct a user relationship diagram and combining the Naive Bayes method, automatic classification of the electronic mails is realized, an accuracy rate of a classification system is improved, and a misjudgment rate is reduced. Through the method, a confidence factor is proposed to estimate credibility of a classification result of a Naive Bayes classifier, the Naive Bayes method is combined with the user relationship diagram, the user relationships contained in the normal mails are utilized to construct the user relationship diagram, and a user white list is generated according to general mail processing habit rules of users. In a new mail classification process, classification results are continuously fed back to the user relationship diagram, the user white list is further updated, so the user relationship diagram and the user white list are automatically adjusted by the classification system according to change of the new mails, and thereby the higher accuracy rate is realized.