Risk management (RM) technique concentrates on the unknown future performance of projects to determine risks, and it suggests early corrective actions to reduce the impacts of the identified risks. Irrespective of the project properties, cost and schedule growths are substantially experienced in construction projects. Some research works developed models without incorporating any direct relation between different project parameters and the project performance. Moreover, other research studies utilized inputs that fall short in covering the varied risks present in construction projects. To this end, no research study is perceived to have established an integrated methodology to predict the performance of construction projects. As such, this paper presents a holistic RM model to predict the project performance by incorporating a wide spectrum of inputs. The paper relies on 25 parameters that are believed to be the most prominent variables affecting the performance of construction projects. These variables were incorporated into a survey to study their effects on project performance. The collected data was used to fit statistical distributions for each parameter. Based on a mapping between the fitted distributions of the 25 parameters and those of the cost and schedule overruns, this research work was able to propose a new RM model that is easily used to predict project performance in terms of cost and time. This research is valuable for the construction industry as it allows decision makers to take corrective actions as well as assessing the impact of such actions on the future performance of projects. Ultimately, project administrators will be able to predict the overall cost and schedule overruns based on various project parameters. This helps in taking the appropriate actions and decisions to ensure smooth delivery and execution of projects.