Raw goat milk adulterated with expired reconstituted milk was rapidly qualitatively discriminated and quantitatively analyzed by an electronic nose combined with a variety of chemometric methods. Expired reconstituted milk was added to raw goat milk in different proportions before being detected using the electronic nose. The volatile components of the adulterated goat milk samples were gathered by the electronic nose. Based on the sensor responses, an electronic nose method for qualitative discrimination and quantitative analysis of adulterated raw goat milk was established through principal component analysis (PCA), Fisher linear discriminant analysis (FLDA) and linear regression fitting analysis. The results showed that both PCA and FLDA could discriminate among different proportions of adulterated raw goat milk, but FLDA was more effective than PCA. The correlation coefficient of linear regression analysis was 88.4%, and the predicted values and the actual adulteration values showed a linear relationship, indicating that the model has better generalization ability. Thus electronic nose is a feasible approach for rapid qualitative discrimination and quantitative analysis of adulterated raw goat milk.