Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 11 4 2026 10 07 436 457 SACHIN KUMAR Department of Biostatistics and Helath Informatics, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow Anup Kumar Sanjay Gandhi Post Graduate Institute of Medical Sciences Chandra Yadav Principal Biostatistician Pfizer India 237, Anna Salai Chennai - 600 006 Tamil Nadu Amit Misra Department of statistics, Babasaheb Bhimrao Ambedkar University Jai Kishun Department of Biostatistics and Helath Informatics, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow Jai Kishun Department of Biostatistics and Helath Informatics, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow 2025 01 24 2025 11 18 Background:-The duration of post-partum amenorrhea (PPA), a crucial aspect of reproductive health, re- mains a significant factor in family planning and maternal well-being. Understanding the distribution of this period provides valuable insights into fertility patterns and informs contraceptive strategies. However, this dura- tion often involves current status data, presenting challenges in accurate estimation and analysis. Objective:-This study aims to employ statistical modeling, specifically utilizing the Weibull distribution and the EM algorithm, to estimate parameters related to PPA duration. The primary objective is to develop a robust methodology for parameter estimation within current status data. Methodology:-The research employs the Weibull distribution, known for its applicability in current status data analyses, as a framework for modeling PPA duration. Leveraging the EM algorithm, the study develops an approach to estimate the Weibull distribution parameters from the current status data. This methodology focuses on overcoming the challenges posed by interval-censored observations, providing a more accurate understanding of the duration. Result:-The application of the EM algorithm to estimate Weibull distribution parameters yields promising results. The methodology successfully addresses the complexities of current status data, offering estimates that enhance the understanding of PPA duration. The results highlight the efficacy of the proposed approach in handling such nuanced datasets. Conclusion:- This study underscores the significance of statistical modeling techniques, particularly the Weibull distribution coupled with the EM algorithm, in estimating parameters for PPA duration analysis. The successful application of this methodology emphasizes its potential for furthering the understanding of fertility patterns and aiding in informed decision-making concerning reproductive health strategies.   https://jbe.tums.ac.ir/index.php/jbe/article/view/1580