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Objective: To investigate the correlated factors of fungal rhinosinusitis and to analyze its clinical features. Methods: A group of 150 patients with fungal rhinosinusitis treated by surgery and another group of 150 patients with chronic rhinosinusitis in our hospital were selected and their clinical data were analyzed and compared retrospectively. The multiple factor Logistic regression analysis and square test were used to analyze the clinical data of all the patients. The correlated factors and the clinical features of fungal rhinosinusitis were investigated. Gomori methenamine silver staining which was special for fungi was used to classify the pathological types of 150 patients with fungal rhinosinusitis. Results: Age（x1）, the course of the disease（x2）, haem-nasal discharge（x3）, headache（x4）, unilateral/bilateral sinus lesion（x5） and calcified plaque in CT scan（x6） were set as the concomitant variables respectively, and then we established the Logistic regression predictive equation for fungal rhinosinusitis, which was y=-8.714+1.201 x1+0.497 x2+4.576 x3+1.188x4+2.697x5+4.118 x6, P=exp（y）/[1+exp（y）]. The P value meant the probability of suffering fungal rhinosinusitis. Compared with chronic rhinosinusitis, the clinical features of fungal rhinosinusitis were female, over 40 years old, the course of disease <3 years, headache, haem-nasal discharge, unilateral sinus lesion and calcified plaque in CT scan（P<0.05）. Among the 150 patients with fungal rhinosinusitis, 46 cases were chronic invasive and 104 were non-invasive. Conclusions: The clinical features of fungal rhinosinusitis can be predicted by using the suitable logistic predictable equation and they are significant for the diagnosis of fungal rhinosinusitis. [ABSTRACT FROM AUTHOR]