In this article, we investigate parameter estimation for two Lomax exponential distributions under a joint Type-II censoring scheme. This distribution is a flexible model capable of representing lifetime data with both increasing and decreasing trends. Using the Expectation Maximization algorithm, we derive the maximum likelihood estimators for the parameters. We also compute approximate confidence intervals based on the missing information matrix. To evaluate the performance of the proposed method, we conduct a Monte Carlo simulation study across various sample sizes and demonstrate its practical utility through the analysis of a real dataset.
