The aim of this project was to investigate a potential connection between a molecule's capacity to penetrate the blood-brain barrier and its electrostatic potential on the surface of the molecule. A molecule's capacity to penetrate the blood-brain barrier is quantified by their log BB value. This was done by creating a set of 58 molecules, divided into a test set and a calibration set, in Gaussian 16. The molecules were then optimized and their quantum chemical properties were calculated by using HS-95. By using stepwise regression in both Matlab and Excel these different parameters were then used to search for a correlation between the parameters and experimental log BB values. This resulted in an equation with 10 variables with an adjusted R2 value of 0,6456. When tested against the test set the mean fault was 0,1443. Outliers were then identified and removed and stepwise regression was executed once more. This resulted in an equation with 10 variables with an adjusted R2 0,8749. When this was tested against the test set the mean fault was 0,0798. The results showed that the variables that were important were the electrostatic potential, surface area and volume.