Abstract DNA can adopt structures in solution apart from the well-known Watson–Crick double helix, ranging from disordered single strands to high-order structures such as triplexes or quadruplexes. Moreover, different topologies can be adopted depending on the polarity of the DNA strands. The elucidation of the structure and topology adopted by a DNA sequence is usually carried out by means of spectroscopic techniques, such as circular dichroism. In this work, the ability of several chemometric methods to efficiently classify DNA structures from circular dichroism data is tested. With this objective in mind, a dataset including 50 experimental spectra corresponding to different DNA structures (random coil, duplex, hairpin, reversed and normal triplex, parallel and antiparallel G-quadruplex, and i-motif) has been analyzed by means of unsupervised hierarchical clustering analysis, principal component analysis and partial least squares discriminant analysis. The results have shown than those methods allow efficiently the classification of DNA structures from circular dichroism spectra. Moreover, these classification methods also provided the most characteristic wavelengths used in the classification procedures.