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The purpose of this study is to predict HbA1c in diabetics. The obstacles behind the prediction of HbA1c is the limitations in the laboratory to provide services for diabetics regarding HbA1 check-up. HbA1c prediction is made by a combination of K-Means and C4.5 methods. K-Means is used to classify continuous data. From the results of the K-Means classification will be used by C4.5 to create a rule (decision tree). The prediction results obtained will be carried out as a validation process to determine the level of accuracy by using K-Fold Cross-Validation. The accuracy value obtained is 72%. The resulting benefit from the prediction of HbA1c can be used as an alternative solution to overcome limitations in the laboratory in terms of HbA1c check-up servicing and the results of HbA1c prediction can also be used as a recommendation by doctor in determining the medical decision for diabetics.