This paper presents a statistical analysis of Covid-19 data using a new distribution. Some mathematical properties of the proposed distribution such as survival and hazard functions, quantile function, median, ordinary and incomplete moments, moment generating function, probability weighted moment, distribution of order statistic, and Renyi entropy are derived. Five estimators are examined for unknown model parameters. The performances of the estimators are compared using an extensive simulation study based on the bias and mean square error criterion. Two Covid-19 data sets representing the percentage of daily recoveries of Covid-19 patients are used to illustrate the utility of the new distribution. The results show that the new model is a superior alternative for some current models with bounded support.