This study aims to identify the pattern and distribution of diseases at the Mambi Health Center using the K-Means Clustering method. Patient data includes age, gender, address, and type of disease suffered. This method was chosen because of its ability to group data based on similar characteristics, making it easier to identify dominant diseases. The results reveal the age groups susceptible to certain diseases, the geographical distribution of diseases with high prevalence, and the types of diseases often encountered at the Puskesmas. These insights are expected to help Puskesmas in allocating resources effectively, designing more appropriate prevention programs, and improving the quality of health services. This study also provides recommendations for disease management strategies based on the identified groups, so as to support efforts to improve public health.