Smell and taste, two fundamental senses among the five, play an essential role in detecting and recognizing chemicals. Scientists and researchers are intrigued by the complex nature of the sense of smell and its close relationship to memory and emotions; moreover, they have consistently endeavoured to investigate its underlying mechanisms. In the olfactory epithelium, which is located in a 3.7 cm 2 region in the upper nasal passageways, olfactory receptor neurons interact with volatile odorant molecules to help perceive odors. . Linda Buck and Richard Axel's Nobel Prize-winning research uncovered olfactory receptors (ORs), which are members of the G-Protein Coupled Receptor class . Higher brain regions process the patterns created by the aggregation and transport of signals from activated olfactory neuron circuits to the olfactory bulb. The significant advancements in speech, audition, and vision suggest that the sensory output for olfactory stimuli can be predicted similarly . Recent years have witnessed an increasing interest in leveraging data-driven approaches, particularly in the realm of machine learning, for predicting structure-odor relationships . Numerous endeavours have aimed to showcase the viability of predicting olfactory perception using structural features, typically encoded by molecular fingerprints, mass spectra, and vibrational spectra of the odorant molecules . Among these works, datasets, features and classification approaches differ significantly.