Abstract: o probe the application of logistic regression model to the predi ction and control of pneumoconiosis. Methods: Multi-logistic regression was used to establish a regression model formed by three factors and pneumoconiosis prev alence probabilities. The three factors are exposure time (ET) of workers to the dust, the average exposure concentration (AEC) by exposure ages, and dust toxic ity (T). Results: (1) The regression model for the prediction and control of pne umoconiosis is P＝1/｛1＋exp［-(-5.4707＋0.0947ET＋0.0024AEC＋1.9784T)］｝. ( 2) The odds rates of these three factors affecting the pneumoconiosis prevalence come respectively as follows: 1.0994(ET), 1.0024(AEC) and 7.2310(T). Conclusion s: The high conformability of the regression model for the prediction and contro l of pneumoconiosis with the subject groups suggests its better practicality and application value in the scientific management and the decision-making in the f ield of pneumoconiosis prevention.