Many forms of breast carcinoma are hormone-dependent and therefore development of novel aromatase inhibitors is of particular interest. Since brain metastases are frequent in patients with advanced breast carcinoma, one of the goals of modern drug development is the discovery of drugs with specific pharmacokinetic profile. High performance thin layer chromatography (HPTLC) is often used to determine lipophilicity of the molecules based on their retention constant. As a predictive analysis, multiple linear regression method was performed to connect pharmacokinetic-dependent parameters with independent physicochemical properties such are: R , TPSA and M of fourteen D-ring modified oestrone derivatives. Additionally, docking studies were performed. Conducted correlation analysis indicates excellent dependence between experimental R parameter values and calculated values of pharmacokinetic parameters. Results show sufficient intestinal absorption of all the investigated molecules as well as moderate volumes of distribution and strong affinity for binding to plasma proteins. Crossing blood-brain barrier is predicted to be successful for 11 compounds. The created quantitative structure activity relationship model represents an excellent predictive tool and enables determination of pharmacokinetic properties of examined compounds. Docking analysis defined molecules I and II to be the best candidates; however, compound II violates the Lipinski rule. It has been concluded that molecules with hydroxyl group at C-3 more effectively pass through blood-brain barrier while structures with benzyloxy groups have stronger interactions with CYP1A19. Molecules II , II , II , and II are regarded as most suitable candidates for further investigation considering their good pharmacokinetic and docking characteristics. Copyright © 2017 John Wiley & Sons, Ltd.