The intensification of dairy production to meet global food demand has led to increased occurrence of metabolic disorders in dairy cattle. One example is ketosis, which weakens the animals’ immune function and makes them more susceptible to other disorders if not treated early. For this reason, we developed a Gnu Octave code script to discriminate the metabolic status of dairy cattle, analysing the spectroscopic characteristics of raw milk as per the aquaphotomic approach. The molecular structure of water in milk changes in response to the subtle quantitative alterations in analytes accompanying the initial stages of ketosis. Therefore, the multivariate spectral analysis of the water absorbance model and chemometric models represent a valuable approach for monitoring the production and metabolic performances of the animal that can ensure early recognition of metabolic disorders in intensive cattle farming. Specifically, the implemented code performs pre-processing methods and chemometric analysis to appreciate the hidden information within the milk sample’s raw spectral data. This study describes the preliminary results of applying such a technological solution in three dairy cattle farms in the Lombardy region.