Modelling of QT-prolongation has been performed using data for 19 structurally diverse hERG K+ channel blocking drugs taken from literature. The modelling used hydrophobicity corrected for ionisation (log D) and various 2D and 3D physico-chemical molecular descriptors. Stepwise regression produced a two parameter, interpretable and transparent QSAR with good statistical fit, including log D and the maximum diameter of molecules (Dmax). Two strategies were applied for model validation: (i) a scrambling procedure, i.e., training the total set of 19 chemicals after randomising the hERG K+ channel blocking activity data and (ii) use of external validation sets. Validation of the models showed them to be stable and statistically significant. The effect of molecular size on QT-prolongation side effect is discussed.