Appropriately selected analytical methods combined with multivariate techniques are valuable in the classification of milk and dairy products for authentication/adulteration, allowing food safety diagnoses. In addition to the use of SIR analysis by IRMS, MEC is also frequently quantified using analytical methods/techniques, e.g. AAS, ICP–MS and ICP–AES. To improve the efficiency of the milk data obtained, a combination of IRMS with the abovementioned analytical techniques has been applied. However, combined techniques, such as SN–ICP–MS, LA–ICP–MS, MC-ICP-MS and 1H NMR are used less frequently. With such methodical combinations, it has been possible to achieve a more advanced assessment of the authentication/adulteration of milk and its products. Computational techniques, e.g. PCA, FA, CA, DA, PLS, PLS–DA, SIMCA and ANN, have been helpful in classifying milk and its products in terms of their geographical provenience, the type of milk product, the feeding system, the degree of environmental pollution, etc. The data obtained are useful for obtaining deeper insights into the principles of the mineral composition of foods and are useful in detecting mislabelling of products to preserve the brand reputation of original products as well as to protect the consumer from financial harm. The application of chemometric tools has led to a deeper understanding of the distribution of mineral components in foods, especially with respect to geographical provenance and the type of milk and its products.