A method of applying maximum entropy probability density estimation approach to constituting diagnostic criterions of oil monitoring data is presented. The method promotes the precision of diagnostic criterions for evaluating the wear state of mechanical facilities, and judging abnormal data. According to the critical boundary points defined, a new measure on monitoring wear state and identifying probable wear faults can be got. The method can be applied to spectrometric analysis and direct reading ferrographic analysis. On the basis of the analysis and discussion of two examples of 8NVD48A-2U diesel engines, the practicality is proved to be an effective method in oil monitoring.