These papers aim to study the estimation of the simple linear regression equation coefficients using the least square method at different sample sizes and different sampling methods. And so on, the main goal of this research is to try to determine the optimum size and the best sampling method for these coefficients. We used experimental data for a population consist of 2000 students from different schools all over the country. We had changed the sample size each time and calculate the coefficients and then compare these coefficients for different sample sizes with their coefficients of the real population; and the results have been shown that the estimation of the linear regression equation coefficients are close from the real values of the coefficients of the regression line equation for the population when the sample size closes the value (325). As it turns out that the Stratified random sampling with proportional distribution with class sizes gives the best and most accurate results to estimate linear regression equation with least square method.