The wind energy is one of the most significant alternative clean energy source and rapidly developing renewable energy sources in the world. For the evaluation of wind energy potential, probability density functions (pdfs) are usually used to model wind speed distributions. The selection of the appropriate pdf reduces the wind power estimation error and also allow to achieve characteristics. In the literature, different pdfs used to model wind speed data for wind energy applications. In this study, we propose a new probability distribution to model the wind speed data. Firstly, we defined the new probability distribution named Poisson-Gamma (PG) distribution and we analyzed a wind speed data sets which are about five pressure degree for the station. We obtained the data sets from Turkish State Meteorological Service. Then, we modelled the data sets with Exponential, Weibull, Lomax, 3 parameters Burr, Gumbel, Gamma, Rayleigh which are used to model wind speed data, and PG distributions. Finally, we compared the distribution, to select the best fitted model and demonstrated that PG distribution modeled the data sets better.