The quality and precision of tracking manuevering targets under large clutter is highly dependent on both the data association and state estimation algorithms. In this study, measurement-to track association problem was discussed and the optimal association problem was shown to be a Markov Decision Process. The problem model considers the batch measurements in a time interval. The optimization problem has an heavy computational load, therefore the rollout algorithm is used to solve this problem. The approximate solution to the association problem is a new approach and it does not exist in the literature. The algorithm was applied to a tracking scenario and its efficiency is demonstrated in the simulations part.