**Abstract**

In this study, 29 volatile alkylated phenols were subjected to a quantitative structure retention relationships (QSRR) studies; we have developed two- and three-dimensional quantitative structure retention relationships (2D- and 3D-QSRR) for this series; and these molecules were subjected to a 2D-QSRR analysis for their retention property using stepwise multiple linear regression (MLR) and 3D-QSRR analysis using partial least squares (PLS). The 28 descriptors are calculated for the 29 molecules using the ChemOffice and ChemSketch software to construct 2D-QSRR model. The 3D-QSRR models were constructed using comparative molecular field analysis (CoMFA) method. The models were used to predict the linear retention indices of the test set compounds, and agreement between the experimental and predicted values was verified. The statistical results indicate that the predicted values are in good agreement with the experimental results (r2 = 0.980; r<sup>2</sup> CV = 0.977 and r<sup>2</sup> = 0.998; r<sup>2</sup> CV = 0.959 for MLR and CoMFA methods, respectively). To validate the predictive power of the resulting models, external validation multiple correlation coefficient was calculated; in addition to a performance prediction power, this coefficient has a favorable estimation of stability for the two methods (rtest = 0.938 and rtest = 0.955 for MLR and CoMFA methods, respectively).

**Keywords:** quantitative structure retention relationship, linear retention indices, multiple linear regression, molecular field analysis, external validation, alkylated phenols
