Projects delays are among the major challenges experienced in construction sector globally, attributed the sector’s complexity and unpredictable nature. As such, adopting Artificial Intelligence techniques which have evidenced its capacity to solve such vigorous, ambiguous and intricate tasks within the construction sector is imperative. The goal of this study is to develop a machine learning model that can accurately analyze and predict delay risk in Zimbabwe’s road construction projects utilizing objective data sources. Ultimately, the presented research leverages the power of machine learning to facilitate a robust technique for project delay prediction that contributes to construction project management monitoring and sustainability.