Objective To analyze the influencing factors of fetal chromosomal abnormalities by logistic regression model and Chi-squared Automatic Interaction Detector (CHAID) decision tree model, and compare the advantages and disadvantages of the two statistical methods. Methods The data of 642 singleton pregnant women with positive ultrasound soft marker and amniocentesis results were retrospectively analyzed,with fetal chromosomal abnormalities as the dependent variable and ultrasound soft marker as independent variables, logistic regression model and decision tree model had been established to screen the factors affecting fetal chromosomal abnormalities, and receiver operating characteristic (ROC)curve was drawn in order to see the differences of the effects of the two models. Results The univariate logistic regression model showed that the nuchal translucency thickening, absent nasal bone, and ventriculomegaly were the risk factors for fetal chromosomal abnormalities. Three factors were used to fit the regression model, these factors including nuchal translucency thickening（OR=7.511，P<0.05）, absent nasal bone (OR=4.819，P<0.05) and ventriculomegaly (OR=4.789，P<0.05) were selected by the multivariate logistic regression model. The decision tree model showed that the nuchal translucency thickening and absent nasal bone were the influencing factors of fetal chromosomal abnormalities. The ROC curve area of the logistic regression model was larger while that of the decision tree model show a smaller area (0.712vs 0.675，Z=2.267，P<0.05). Conclusion Logistic regression model and decision tree model have certain value in analyzing the relationship between USM and fetal chromosomal abnormalities, and the logistic regression model is better than the decision tree model. Key words logistic regression model; CHAID decision tree model; fetal chromosomal abnormality; ultrasound soft marker