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Introduction: Longitudinal studies widely used in many branches of science, especial-lly medical science. In the past two deca-des, many models have been proposed for the evaluation of such data. These models are also developed to investigate various re-sponse variables such that categorical varia-bles that have many applications in medical research. While many papers have comp-ared the marginal and random effects mo-dels but fewer studies have compared the marginal and transition models. Materials & Methods: This paper used simulation with different scenarios for corr-elation, sample size and repeated measures and calculated ROC Curve for two models. Then estimated AUC for them and comp-arison was performed. Findings: If intensity transition for healthy to disease was large and patient remained disease for a long time that is better used transition model to prediction. In addition, in conditions that intensity transition in any status was equal or trends of transition inte-nsity was inverse of position1 that healthy people remained health for a long time and patients recovered quickly, that is better used marginal model. Discussion & Conclusion: In analysis of longitudinal data for achieving more accur-ate results when purpose of study was pred-iction, that is better intensity transition bet-ween status was considered and then dec-ided which model is choosen.