In this article, we explore the estimation of parameters for the Lomax exponential distribution, which is a flexible model used for modeling lifetime data with both increasing and decreasing shapes. We focus on the type-II censoring scheme and derive the maximum likelihood estimator of the parameters using the Expectation- Maximization algorithm. We also calculate approximate confidence intervals based on the missing information matrix. To evaluate the e activeness of our proposed method, we conduct a Monte Carlo simulation study with varying sample sizes, and we demonstrate its usefulness by analyzing real dataset.
