Effective construction waste (CW) management, mainly concrete, brick, and steel, is a critical challenge due to its significant environmental and economic impacts. This study addresses this challenge by proposing multiple linear regression models to predict waste generation in residential buildings within the Egyptian construction industry, considering the influence of factors such as building design and site management features. Using data from 25 case studies, the models demonstrated high predictive accuracy, with adjusted R² values of 0.877, 0.893, and 0.889 for concrete, bricks, and steel waste, respectively. These R2 values indicate that the models explain approximately 88–89% of the variance in waste generation in residential buildings, highlighting their effectiveness in enhancing resource planning and waste management strategies. The findings suggest that incorporating variables such as total area, design consistency, and site organization significantly improves the accuracy of waste predictions. The models offer valuable insights for enhancing construction practices, minimizing waste, and supporting sustainable development in Egypt’s construction industry.