In the present paper, the surface-enhanced Raman spectroscopy (SERS) was used to build the model for the quantitative detection of ethyl paraoxon by the principal component analysis and segmented linear regression (PCA-SLR). Firstly, SERS in 820～1 630 cm-1 of ethyl paraoxon solution were measured and the spectra in 820～1 630 cm-1 (complete range) and 845～875 cm-1 (characteristic range) of ethyl paraoxon solution were preprocessed by standard normal transformation (SNV), multiplicative scatter correction (MSC), the absolute values of first derivative and the second derivative respectively. Additionally, the number of dimensions of the spectra was reduced by PCA. Finally, the models were established by SLR. It was found that the model developed with MSC preprocessed spectroscopy of characteristic range performed best (RMSEP: 0.33) by comparing the predictive accuracy of the different models. The result could meet with the needs in the quantitative detection of ethyl paraoxon.