الفهرس 
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Abstract
Several techniques were adopted carefully to identify the factors that affect the cost of construction materials at early-stage through reviewing previous studies and expert’s interviews. Forty-six factors were collected and categorized to eight groups. Twelve factors that have the greatest effect were identified. These most important factors were used for developing models by using regression analysis and artificial neural network. Two software (SPSS version 24 and Neural Power Professional Version 2.50) were used for developing the desired models. These models used the twelve input parameters to predict the cost of construction materials “sand, gravel, cement, reinforced bars (output). The required information was collected from 73 real construction projects in Egypt. The proposed models were tested. where the results illustrate the accuracy of the models to predict materials cost.