This paper explains how machine learning can improve risk assessment in road construction. Traditional methodsdependonhuman judgment and often miss complex risks. The study uses data from past projects, sensors, drone images, and BIMmodelstotraindifferent machine learning systems like neural networks and decision trees. These models can better predict cost andtimeoverruns,detect structural problems early, and find on-site hazards faster. The paper also suggests using federated learning to protect dataprivacy.Overall, machine learning helps make road construction safer, quicker, and more efficient. Keywords: Road Construction, Risk Assessment, Machine Learning, Deep Neural Networks, Gradient Boosting, LSTM, GraphNeuralNetworks, UAV Imagery, Building Information Modeling (BIM), Federated Learning