In recent years, just as there has been a trend towards digitalization in every field, digitalization has also gained greater momentum in healthcare services. This acceleration started with the Covid-19 pandemic and people wanting to receive healthcare services remotely, with the aim of reducing virus transmission. As a result of providing health services remotely with digital technology, it has brought many problems and made many innovations and developments necessary. One of the most important of these problems is the dynamic planning of doctor appointments in the most efficient way. It has been determined that this situation is a significant problem in almost all developed countries. Online doctor consultation systems have emerged as an effective solution to facilitate remote medical consultations and access healthcare. However, the appointment scheduling process in these systems often lacks optimization, resulting in suboptimal patient and doctor experiences in digital health systems. This study demonstrated how fuzzy logic can be applied to determine optimal appointment time slots in online doctor appointment systems. With fuzzy logic methodologies, patient preferences, doctor’s workload models, patient urgency levels and doctor’s areas of expertise are classified. This study aimed to determine the most appropriate appointment time intervals that will maximize patient satisfaction while ensuring efficient use of limited physician resources. The results of the study showed the effectiveness of fuzzy logic in optimizing appointment scheduling efficiency and improving the overall quality of online doctor consultations.