Introduction: Current methods for olfactory assessment are often time-consuming and necessitate the involvement of an examiner for both administration and documentation of responses. This study aimed to evaluate the clinical utility of a novel digital olfactory device, the MultiScent-20 odor identification test (MultiScent-IT), in distinguishing individuals with olfactory dysfunction from those with normal olfactory function. Materials and Methods: The work was conducted and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement for case-control studies. The test was administered to individuals with olfactory dysfunction (cases) and normosmic volunteers (controls), who were classified using the Sniffin' Sticks threshold test. Results: A statistically significant difference was observed in the total test scores between cases (9.6 +/- 4.5) and controls (13.2 +/- 1.9), p = 0.01. The test performance, defined as (total score/total time) x 100, was significantly lower in cases (1.9 +/- 1.4) compared to controls (3.2 +/- 1), p = 0.016. A receiver operating characteristic curve analysis demonstrated an area under the curve of 0.749, indicating a fair to good ability of the MultiScent-IT to discriminate between the groups. A MultiScent-IT score below 10 demonstrated perfect sensitivity (100%) in detecting olfactory dysfunction. Significant correlations were identified between the MultiScent-IT score and the Sniffin' Sticks threshold score (p = 0.009, r = 0.524), as well as the Portuguese version of the Olfactory Disorders Questionnaire (PT-ODQ) score (p = 0.013, r = -0.423). Conclusion: MultiScent-IT is a promising tool for differentiating between individuals with and without olfactory dysfunction in clinical settings.Our sense of smell is important for enjoying food, detecting dangers like smoke, and even forming memories or dealing with emotions. However, smell tests used by doctors can be difficult to perform and may take a long time. This study investigated a new, digital smell test called the MultiScent-IT. This test uses a tablet-like device that releases different smells. We wanted to see if this new test could accurately identify people with a poor sense of smell. We asked people with and without smell problems to take the MultiScent-IT. The test results showed that people with a poor sense of smell scored lower on the test. We also found that the lower a person scored on the MultiScent-IT, the more their smell loss affected their daily life. This new digital test could be a useful tool for doctors. It is quick to use, easy to understand, and does not require special training. This could help doctors identify people with smell problems more easily and track their progress over time. In the future, this type of technology might even be used with artificial intelligence to help diagnose and treat smell disorders more effectively.