Spectrometry technologies combined with hyperspectral imaging have been used for decades in a wide range of applications for scientific, clinical and commercial uses. These include satellite imaging, food quality control, and pathogenic and diagnostic analysis, among others. Recently, the utilization of mass spectrometry and hyperspectral imaging with human fingerprints has increased. Many studies showed that it is possible to obtain detailed information about lifestyle, age, gender, and even medication and drug consumption quickly and noninvasively from an individual fingerprint. This study discusses analyzing human fingerprints using Matrix Assisted Laser Desorption Ionization Mass Spectrometry (MALDI MS) and hyperspectral imaging techniques to detect caffeine consumption and determine the region of origin of each person. To achieve this, an experiment with six volunteers from two countries was conducted. Participants were asked to donate their fingerprints twice, before and after coffee consumption. This study demonstrates the experiment preparation steps from fingerprint acquisition to obtaining individual spectral data, preprocessing steps applied to overcome problems and issues raised during the experiment, and classification methods. The methods used were: multivariate regression, principal components regression, and partial least square discriminant analysis. For each classification method, two models were generated to differentiate between the groups: caffeine/non caffeine and individuals from different countries. The results showed good classification of the groups, but due to experiment limitations, especially low sample number, it cant be proven that these results represent an actual difference between groups. Its highly likely these results have been generated randomly by overfitting all data points. This conclusion is supported by variable selection results which showed different variables from prior chemical knowledge, and by statistical tests results; therefore, some recommendations were discussed.