The objective of this research is to compare point and interval estimation methods for the population proportion. Three methods of point estimation: Maximum likelihood method, Bayesian method and Minimax method, and three methods of interval estimation: Normal method, Score method and Score continuity corrected method are considered. The lowest mean absolute error and the lowest average width are used as the criteria to selection for point and interval estimation, respectively. The comparisons are done by using three levels of sample sizes (n): small �medium �and large �whereas the population proportions are 0.02, 0.04, 0.06, 0.08, 0.1, 0.3 and 0.5, all of which are considered at 90%, 95% and 99% confidence levels. This research uses the Monte Carlo method. The experiment is repeated 1,000 times for each condition. The results of this research are as follows. For point estimation, all sample sizes, we recommended Maximum likelihood method should be considered. In the case of interval estimation, for all sample sizes and confidence levels, Normal method should be used when �and Score method is suitable for another cases.