In order to improve the economic and social qualities of Egyptian families and raise their standard of living, one of the most important goals of state policy is to identify the social, economic, and environmental characteristics as well as the factors that influence fertility and its decline trends at various levels. The current study aimed to identify the change in the number of children per woman in Egypt. An unconventional method that has not been used before in Egypt was applied to measure fertility levels in Egypt and predicts the factors that positively affect the reduction in the number of births per woman. There are many traditional methods that can measure fertility levels in Egypt and have been widely used in many literatures, but the current study uses the artificial intelligence method, specifically neural networks, to predict demographic and socio-economic variables that will have a significant impact on reducing the number of children per woman during her reproductive life. The artificial neural network methodology will analyze and predict the most important factors that can affect the number of children in Egypt. Data from - Health Survey for the Egyptian Households 2021 were used. The results of the study indicate that partner's occupation, wealth index quintile, ideal number of children, residency region, and partner's educational attainment are the most significant factors influencing the number of births.

KEYWORDS: Artificial Neural Networks, fertility level, Predicting, Multi-layer Perceptron algorithm, artificial intelligence.