Allergenic pollen grains cause seasonal allergic rhinitis and asthma. During pollination season these airway diseases affect roughly a quarter of European population, causing multibillion costs in medical treatments and reduced work productivity, and thus monitoring systems for timely hay fewer forecasts are of outmost importance. In addition, analysis of airborne pollen can provide valuable data in studies of environmental and climate change. This is especially important for countries such as Croatia, with significant surface area covered by forests, where valuable forest resources require constant monitoring. An automated black-box approach with an inexpensive and rapid identification method is therefore highly desirable. The last decade saw a growing number of experimental works dedicated to simple and inexpensive pollen identification method based on vibrational spectra of pollen samples. The proposed research is focused on development of a novel methodology for quantitative and qualitative pollen identification that uses vibrational spectroscopies and chemometrics. Practical spectroscopy-based identification methodology for pollen would be of great of great importance for Croatia due to its feasible application in environmental studies, such as forest management, monitoring of aeroallergens and invasive species, and phenology.