Soudabeh Semsarian - In order, M.sc. student and faculty member of Agricultural Science University of Zanjan, Zanjan, Iran
Morad Pasha Eskandari Nasab - In order, M.sc. student and faculty member of Agricultural Science University of Zanjan, Zanjan, Iran
Saeed Zarehdaran - Department of Animal Science, Faculty of Agriculture and Natural Resources, University of Gorgan, Iran
Amir Ahmad Dehghani - Department of Water Engineering, Gorgan University of Agricultural Sciences and natural Resources, Gorgan, Iran

Traditional poultry production has changed to a considerable industry after few decades. Now, poultry industry is one of the main sectors to obtain the required protein for human consumption. Prediction of the weight and number of eggs according to economic traits can improve the efficiency of production and the profit of producers. In present study, the weight and number of eggs in Mazandaran native fowl were predicted using artificial neural network (ANN). The information of BW at birth, ۸ and ۱۲ weeks of age, weight and age at sexual maturity and the polymorphism of prolactin gene were used for the prediction. The results showed that ANN is reliable method for predicting the weight and number of eggs based on available information

Egg number, Egg weight, Neural network, prediction