Disclosed is a discrimination method for disease degree of large yellow croakers infected with Cryptocaryon irritans, and the method relates to large yellow croakers. The method comprises firstly performing data preprocessing, building a mathematical method by using the 14 impact factors, and building a dimensionality reduction method. The method has features of being quantitative in discrimination, simple and convenient, and high in accuracy and reliability. Random sampling test shows that by use of the method, the severe degree of disease of large yellow croaker infected with Cryptocaryon irritans can be accurately determined by use of measured values of water environment factors, and the accuracy rate is up to more than 90%. The method can be applied to determine the sea area and severity of possible Cryptocaryon irritans infection, and used to direct the prevention and control of Cryptocaryon irritans infection in large yellow croakers. The method is suitable for discrimination on occurrence of Cryptocaryon irritans infection, and also provides an important reference for Cryptocaryon irritans infection in other marine fishes.