Introduction: Globally, commuting accident risks are always neglected in an organisation. There is a need to assess the impact of commuting accidents based on sociodemographic, human, vehicle, road, and environmental factors and to find suitable and effective mitigation strategies to alleviate the associated undesirable outcomes. Methods: This research was designed to develop a mobile application to assess commuting accident risk levels using artificial intelligence principles, as we are now in the 21st-century technology era. A total of 216 respondents from private and government industries participated in this study. Besides, to prove the developed application’s effectiveness, the study evaluated the effectiveness of the identified risk factor in determining the level of commuting risks predicted by respondents with the risk level calculated by the mobile application. Results: A major contribution of this paper is the effectiveness and accuracy of a mobile application known as CommuRisk. The app was developed using Android Studio and natively uses Java. There was a significant difference between with and without mobile applications in determining the level of commuting risks, and the effectiveness was proven with a (p-value = 0.001) at a 95% confidence interval with large sample size. Conclusion: Thus, this paper proved the effectiveness and accuracy of a mobile application in calculating risk levels exposed by commuters compared to risk levels predicted by commuters.