In many applied areas there is a clear need for extended forms of
the well-known distributions. Generally, the new distributions are
flexible to model real data that present a high degree of skewness
and kurtosis. Each of them is applied to solve a particular part of the
classical distribution problems. In this paper, the new Extended Exp-
G family of distributions is going to be introduced. In particular, G
has been considered as the normal distribution and also Weibull distribution.
some statistical properties such as moments, Maximum
likelihood estimator and regression model have been calculated. The
fitness capability of this model has been investigated by fitting this
model and others based on real data sets. The maximum likelihood
estimators are assessed with simulated real data from proposed
model. We present the simulation in order to test validity of maximum
likelihood estimators.