If no experimentally determined structure of a compound is available or alternative conformations are needed, conformers of the molecule can be generated by computational means. A large number of conformer generation approaches have been developed for small organic molecules in the past decades. Two main search strategies are used to generate a conformational ensemble: systematic and stochastic. In the first approach, each rotatable bond is sampled systematically in discrete intervals, limiting the use to molecules with few rotatable bonds. Stochastic methods on the other hand sample the conformational space of a molecule randomly and can thus be applied to more flexible molecules. Recently, we have combined the stochastic-search method distance geometry, which is computationally efficient, with experimental torsion-angle preferences obtained from small molecule crystallographic data to improve the quality of the generated conformers . The torsion angles were described by a series of hierarchically structured SMARTS patterns developed by Schärfer et al. [J. Med. Chem. 56, 2016 (2013)]. The new approach termed ETKDG has been implemented in the open-source cheminformatics library RDKit and is freely available to the community.