Sigmoid growth models play an important role in describing many natural events that have a sigmoidal curve (S-shaped). In this paper, the two sigmoid growth models based on Burr Type XII distribution called the Burr 1 Type XII and Burr 2 Type XII sigmoid growth models are proposed to be able to describe various situations with accuracy. The methods of estimation of the non-linear least squares and maximum likelihood are used to estimate the parameters of the proposed models. The performance of the new proposed models is investigated and compared with the classical sigmoid growth, Brody and Weibull models in describing the growth of confirmed new cases of COVID-19 in Egypt. The results showed that the new proposed model, Burr 1 Type XII sigmoidal growth is superior over the other models with respect to the coefficient of determination , mean squared error, root mean squared error, model efficiency, and the Akaike information corrected criterion especially when NLS estimation is used.