The X-Gamma Lomax (XGLo) distribution, a new three-parameter modification of the Lomax distribution, was introduced and examined in this study. This distribution's features for reliability and hazard rate are addressed. The methods for estimating the XGLo distribution parameters using maximum likelihood estimation (MLE) and maximum product spacing (MPS) are explained. To compare the MLE and MPS estimate approaches, a numerical investigation is conducted Monte-Carlo simulation. Three real data sets as the cancer data includes failure rates in weeks, 109 days of continuous coal mining occurrences in Great Britain, and remission periods (in months) of a random sample of 128 bladder cancer patients. are used to examine the adaptability and potential of the XGLo distribution. The likelihood ratio test and Kolmogorov- Smirnov test have been used to check the XGLo model is better fits than Lomax model.