Introduction: Type-2 diabetes is one of the most common metabolic diseases characterized by elevated blood sugar levels in the body. The disease is caused by lost insulin sensitivity and insufficient insulin production, which leads to an increase in sugar levels in the blood. Lifestyle interventions such as physical activity, good eating habits and weight loss are important factors that play a crucial role in the treatment of type 2-diabetes. In most cases, they need medication to lower blood sugar level. Gliclazide is a medicine used in many countries for the treatment of type-2 diabetes if metformin, the first line treatment, do not have a sufficient effect. Gliclazide is available in two formulations: immediate release (IR) and modified release (MR) tablet.  Aim: The aim of this study was to develop a model that describes the pharmacokinetics of a gliclazide (IR) tablet based on prior knowledge of PK in the MR formulation and using data from previous published studies. Method: Modeling software Monolix was used to find the most appropriate model for describing the pharmacokinetics of gliclazide. During the study, the most common absorption models were examined, e.g., first and zero order absorption with and without time delay, transit compartment, zero order first order absorption in succession and zero order first order absorption occurring simultaneously. The best model was chosen by comparing the so-called Akaike information criteria (AIC) and by visual predictive control (VPC) for all absorption models tested. AIC values for all absorption models tested by Monolix were compared and the absorption model that shows the lowest value of AIC was the best model.  Results: For single-IR data, where each profile corresponded to an individual pharmacokinetic profile, the zero- order absorption adaptation with a delay (Tlag) was the best adaptation. For population IR and population MR data, each pharmacokinetic profile represents an average of all individuals' measured concentrations. The fit for these data showed that zero- order kinetics with a delay (Tlag) was the best fit. Conclusion: In summary, this work showed that the best absorption model that is well adapted to both single and population data for the IR formulation, and that well describes the pharmacokinetics of gliclazide, is a single compartment with zero order kinetics and time delay. The results showed that the best absorption model that is well adapted to population data for the MR formulation is also a one-compartment with zero-order kinetics and time delay.