The goal of the present paper was to develop a quantitative structure–activity relationship (QSAR) method using a simple statistical approach, such as multiple linear regression (MLR) for predicting the blood–brain barrier (BBB) permeability of chemical compounds. The “best” MLR models, comprised log P and either molecular mass (M) or isolated atomic energy (Eisol), tested on a structurally diverse set of 66 compounds, is characterized the by correlation coefficients (R) around 0.8. The obtained models were validated using leave-one-out (LOO) cross-validation technique and the correlation coefficient of leave-one-out- Symbol (Q2) was at least 0.6. Analysis of a case from legal medicine demonstrated informative value of our QSAR model. To best authors’ knowledge the present study is a first application of the developed QSAR models of BBB permeability to case from the legal medicine. Our data indicate that molecular energy-related descriptors, in combination with the well-known descriptors of lipophilicity may have a supportive value in predicting blood–brain distribution, which is of utmost importance in drug development and toxicological studies.