In this work, dielectric spectroscopy (DES) in association with partial least squares (PLS) multivariate calibration method was employed to determine octane numbers (research octane number or RON and motor octane number or MON) of clean gasoline samples. The factor number included in PLS model was obtained according to the lowest sum of squares of predicted residual error (PRESS) in calibration set. The performance of the final model was evaluated according to PRESS and correlation coefficient (R). The optimal factor numbers are 9 in both RON and MON PLS calibration models, which were achieved with PRESS = 2.74 and R = 0.9598 in RON calibration set and the lowest PRESS = 2.72 and R = 0.8983 in MON calibration set. In validation set, PRESS = 1.00 and R = 0.9552 for RON and PRESS = 0.47 and R = 0.9105 for MON were obtained. Results indicated that PLS multivariate calibration models based on DES data were proven suitable as a practical analytical method for predicting octane numbers of clean gasoline. (c) 2009 Elsevier Ltd. All rights reserved.