Purpose : To identify general characteristics of school personnel with recent fatigue which was the most frequent symptom among subjective symptoms and to explore fatigue-related factors by evaluating physical and perceived health status, life style, and symptoms through data mining techniques. Methods : We collected a data of the 1,147(male 545, female 602) who were elementary, middle, or high school personnel, answered a questionnaire, and received physical examination in Seoul School Health Center from September to November in 2000. And we investigated the differences between fatigue group and non-fatigue group for demographic characteristics, physical health status, perceived health status, symptoms, and laboratory values by frequency, chi-square test, t-test, or simple logistic regression analysis by SAS package 8.1, and then selected significant variables as input variables of a decision tree analysis of CART model by SAS E-miner. Results : In general characteristics, the fatigue consisted of 41.1%(male 35.2%, female 46.4%) among 1,147 school personnel. In classical statistics, factors related with fatigue were female, lower means of systolic and diastolic pressure, young age, personnel in middle school, irregular eating habit, no exercise a week or less than 30minutes exercise a day, perception of unhealthy status, and subjective symptoms including short of breath at exercise. In simple logistic regression to examine the relationship between selected independent variables and fatigue as a dependent variable, the odds ratio of gender (female vs male) was 1.58 times, and young age ( 20s vs 60s) 20.67 times, and middle vs high school personnel 1.86 times. However, we mined combined several characteristics by SAS-E miner. In CART model, if health perception was healthy, and age was >= 37.5 years, the proportion of the fatigue was only 19.3%. but if health perception was not healthy and symptom was severe 'short of breath' during exercise and age was < 53.5 years, and BMI was >= 22.69, the proportion of the fatigue was up to 84.8%. Conclusions : The fatigue consisted of 41.1%(male 35.2%, female 46.4%). In classical statistics, fatigue-related factors among school personnel were young age, female gender, perceived unhealthy status, subjective physical symptoms, poor life-style, and lower blood pressure rather than only physical health status. However, in data mining, if health perception was healthy and age was >= 37.5 years, the proportion of the fatigue was only 19.3%. but if health perception was not healthy and symptom was severe 'short of breath' during exercise and age was < 53.5 years, and BMI was >= 22.69, the proportion of the fatigue was up to 84.8%.