This study aims to convert a traditional Lomax distribution into the Stereographically Projected Semicircular Lomax (SSL) distribution by making use of the inverse stereographic projection. The main focus is to semicircularize gathering of data from various applied disciplines to impart flexibility at a higher operational level and, therefore, allow appropriate estimation to be carried out through a flexible model for parameters related to SSL distribution. Further, the entire collection of statistical properties of the proposed distribution has been completely laid out from first principles, including those for the CDF, survival function S(t), and the hazard rate function h(t) in addition to the PDF. There have been two methods adopted for the parameter estimation: Maximum Likelihood Estimation and Cramér von Mises methods. Monte Carlo simulation studies were employed in which several fixed sample sizes were considered in order to analyze the performance of the MLE and CVM methods of parameter estimation. The comparison has been made under the Mean Squared Error (MSE) criterion. The results disclosed that MLE does better than CVM in giving smaller MSE values and hence for estimation.