In order to build the model for predicting the tar content of flue-cured tobacco, multicollinearity of 9 chemical indexes including total sugar (X1), reduced sugar (X2), total nitrogen (X3), nicotine (X4), potassium (X5), chlorine (X6), total sugar to nicotine ratio (X7), total nitrogen to nicotine ratio (X8) and potassium to chlorine ratio (X9) was diagnosed through correlation and statistic test, while the ridge regression between tar content and chemical components was also conducted. The results indicated that collinearity existed among total sugar, reduced sugar, total nitrogen, nicotine, total sugar to nicotine ratio, and total nitrogen to nicotine ratio. And there was extremely significant correlation between the tar content and the 9 chemical indexes mentioned above. Therefore, it was reasonable to establish the multiple linear regression model using 9 chemical components as independent variables based on ridge regression. The prediction model for tar content using ridge regression at parameter K=0.08 was Y = 18.800 9– 0.000 7X1 – 0.034 2X2 + 1.625 2X3 + 0.691 1X4 – 0.968 68X5 + 0.292 70X6 – 0.029 9X7 – 3.519 3X8– 0.056 87X9 (R2=0.817 5), and the regression equation passed the significance test (P<0.01). The regression coefficients properties of ridge regression equation were consistent with the results of correlation analysis, which made the unreasonable symbols of regression coefficients in the least square estimation reasonable.