The accurate identification of clay minerals and associated phases remains challenging, particularly in fine-grained samples with complex assemblages. To assist in their identification, this study introduces MinMatch, a database and automated search program containing over 500 oxide compositions of clay minerals and their associated phases from soils, sediments and rocks. The program compares normalized oxide data with reference entries and ranks potential matches using Pearson correlation coefficients, supported by SiO2:Al2O3 ratios and additional statistical and graphical parameters. Its performance is demonstrated using mineral oxide datasets from well-characterized samples of the 12th Reynolds Cup competition, derived from coarse- and fine-grained separates analysed using energy-dispersive X-ray spectroscopy combined with scanning and transmission electron microscopy. The results show that MinMatch consistently ranks compositionally equivalent minerals among the top matches and successfully discriminates between closely related varieties. The approach provides a rapid, quantitative and reproducible tool for clay mineral studies, complementing X-ray diffraction and other analytical methods.