This paper describes the results of selectivity optimization and internal standard prediction for the quantitation of estradiol and levonorgestrel in transdermal patches by reversed-phase liquid chromatography (RPLC) based on the linear solvation energy relationships (LSERs). The patch samples are prepared by swelling with acetonitrile (ACN) and the separation is performed by Zorbax Eclipse XDB ODS columns. A proper retention range is first determined with a binary mobile phase of ACN and water based on the general resolution equation. The interference to estradiol from a levonorgestrel impurity is then eliminated by a ternary mobile phase of acetonitrile-methanol-water with a composition predicted by LSERs. When the resolution is optimized and the "open window" in the chromatogram for an internal standard is selected, LSERs are used to predict the candidate compounds to be evaluated as the internal standard. The approach described in this study can be used, in general, to considerably improve the efficiency of RPLC method development, particularly for neutral samples. Finally, the LSER approach for the selectivity optimization is compared with a statistical response surface methodology (RSM) based on a central composite design (CCD) in terms of the effectiveness and number of experiments. It is concluded that, although the predicted mobile phase composition to achieve the desired selectivity is about the same, the LSER approach is more efficient and fewer experiments are required.