Stratified sampling enhances the efficiency of estimators by dividing the heterogenous population into the homogeneous strata. In the literature, Stratified Modified Probability Proportional to Size (Stratified MPPS) sampling is a method that selects units within each stratum using MPPS sampling. MPPS sampling is used when the data follows Zipf’s law. In this paper, the allocation methods of sample size among the strata are applied to Stratified MPPS sampling to minimize the variance. Proportional allocation assigns sample sizes to strata in proportion to their sizes and Neyman allocation considers both stratum size and variability among strata to allocate the sample size among various strata. An Empirical study based on real-world datasets, compares the proposed allocation methods to estimate the population total in statistical practice.