The empirical likelihood method is especially useful for constructing condence intervals or regions of the parameter of interest. This method has been extensively applied to linear regression and generalized linear regression models. In this paper; the empirical likelihood method for single-index regression models is studied. An estimated empirical log-likelihood approach to construct the condence region of the regression parameter is developed. An adjusted empirical log-likelihood ratio is proved to be asymptotically standard chi-square. A simulation study indicates that compared with a normal approximation-based approach; the proposed method described herein works better in terms of coverage probabilities and areas (lengths) of condence regions (intervals). 2005 Elsevier Inc. All rights reserved. AMS 1991 subject classication: primary 62G15; secondary 62E20