Many probability models have been developed over the years to model data from various disciplines of human endeavours. There still remain many areas where these existing models cannot be used to model data that arise from these fields. As a result there is a clear need for improvement on the existing ones to ensure they are more flexible in handling various relevant data. This special issue will look into the transmutation of some well-established probability models, establish their mathematical properties such as mean, median, mode,variance,moments, quantiles ,characteristics function and moment generating function.Their order statistics will be given proper consideration ranging from minimum to maximum order statistics. The estimation issues will be addressed using any appropriate estimation method such as maximum likelihood estimation method (MLE).Various areas of applications will be looked into such as reliability analysis, survival analysis, finance, medicine, economics, actuarial science and insurance to demonstrate their applicability and flexibility in statistical analysis of data arising from these fields. Their performances will be tested using the appropriate statistical tests such as Akaike Information Criterion (AIC), Corrected Akaike Information Criterion (AICC) and Bayesian Information Criterion (BIC). These new models will be characterized by relating them to the existing ones in the literature and some theorems will be stated and proved where necessary to establish these relationships. We hope this special issue will provide helps to researchers in this field and other related disciplines as this will birth some new probability models whose properties will be established.

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