labor productivity is an issue of particular importance to the performance of construction projects. Construction labor productivity is affected by numerous factors these factors include motivation. some researches studied the impact of motivation on labor productivity, but most of these studies relied on expert opinions and perceptions rather than empirical data collected from construction sites. The purpose of this study is to investigate the relationship between labor motivation and their productivity. For this purpose, 14 motivational factors that significantly affect labor productivity were identified from literature, and by using a questionnaire survey, they were shortened to 5 critical factors. a productivity model was developed based on artificial neural network (ANN) and multiple linear regression (MLR) to identify the effect of motivation factors on labor productivity. Data related to labor productivity of brickwork and ceramic work crafts in Egyptian construction projects were collected. The results revealed that ANN technique has better prediction performance than MLR. In order to identify the effect of the motivation factors on labor productivity a sensitivity analysis was conducted. This study adds to the body of knowledge in construction project management by evaluating the influence of labor motivation on productivity. The results can facilitate the prediction of labor productivity, which helps with project cost and schedule management.