Construction project control is one of the important issues that is of great importance in the construction industry. Issues such as planning, scheduling, resource management, cost control, risk management, communication and change management are of great importance during the implementation of construction projects. This book examines the use of machine learning algorithms and models to predict the time and costs related to the completion of construction projects. Based on the available data from past projects, these methods examine various factors such as project dimensions, type of work, environmental conditions, etc. and use machine learning algorithms to create a model to predict the time and cost of completing future projects. These methods can help improve the efficiency and productivity in completing construction projects and reduce costs and increase the profitability of projects. Providing accurate cost estimates in construction projects is a difficult task because construction projects are subject to numerous risks and uncertainties. This is especially exacerbated during the project planning stage when sufficient data and information about the projects.