Epidemiological models provide a powerful tool for investigating the dynamics and control ofrninfectious diseases, but quantifying the underlying epidemic structure can be challengingrnespecially for new and under-studied diseases. Measles is a highly infectious disease which hasrna major impact on child survival, particularly in developing countries. The importance ofrnunderstanding the epidemiology of this disease is underlined by its ability to change rapidly inrnthe face of increasing immunization coverage with proper cost effectiveness. Much is still to bernlearned about its epidemiology and the best strategies for administering measles vaccines.rnHowever, it is clear that tremendous progress can be made in preventing death and diseasernfrom measles with existing knowledge about the disease, and by using the presently availablernvaccines and applying well-tried methods of treating cases. Since vaccination turned out to bernthe most effective strategy against childhood disease, developing a framework that wouldrnpredict an optimal vaccine coverage level needed to control the spread of these diseases isrncrucial. We consider an optimal control problem subject to an SEIR measles epidemic modelrnwith vaccination controls. Our aim is find the best optimal control strategies to make the numberrnof infectious individuals as small as possible and to keep the vaccination ratio of measles as lowrnas possible during a certain vaccination period that will minimize the cost of control. We usedrnPontryaginâ€™s maximum principle to characterize the optimal levels of the controls. The resultingrnoptimality system is solved numerically by forward-backward sweep method. The results showrnthat the optimal vaccination policy differs according to the controlled and uncontrolledrnindividuals and has a very desirable effect upon the population for reducing the number ofrninfected individuals. The effect of vaccination on transmission dynamics of measles is studied.rnThe resulting optimality system also showed that, the use of vaccinating at the highest possiblernrate to the population as early as possible is essential for controlling an epidemic of the measlesrndisease. Finally, we use our model to simulate the data of measles cases in the Ethiopia fromrn2004 to 2014 and design a control strategy (optimal vaccination policy) of the country torneliminate the epidemic for the future course with optimal control theory. The results from ourrnsimulation are discussed.