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Digital twins were initially introduced in the aerospace industry, but they have been applied to the medical field in the 2020s. The development of the Internet of Things, sensor technology, cloud computing, big data analysis, and simulation technology has made this idea feasible. Essentially, digital twins are virtual representations of real-world data that can generate virtual outcomes related to a patient based on their actual data. With this technology, doctors can predict treatment outcomes, plan surgery, and monitor patients’ medical conditions in real time. While digital twins have endless potential, challenges include the need to deal with vast amounts of data and ensure the security of personal information. In the field of rhinology, which deals with complex anatomy from the sinus to the skull base, the adoption of digital twins is just beginning. Digital twins have begun to be incorporated into surgical navigation and the management of chronic diseases such as chronic rhinosinusitis. Despite the limitless potential of digital twins, challenges related to dealing with vast amounts of data and enhancing the security of personal data need to be surmounted for this method to be more widely applied.