Precise prediction of certain factors in every industry is very crucial to ensure all materials, equipment and other resources are being used optimally. Systematized analysis and effective management forms basic infrastructure for all businesses and hence, life-cycle costing (LCC) exists to assist most industries to plan and monitor their assets as well as optimise present and future cost for every project to ensure long term profitable investment. To be defined, life cycle costing is related to enhance the value of money in assets management by taking few factors into consideration throughout the operational period of every related project1. In LCC, there are few circumstances and risks that industry should be pondered as this may affect the precision of the results such as uncertainty data sets depending on the scale of the project, cost, operating conditions and economic situations like inflation and taxation. To overcome these circumstances or risks, risk analysis discussed in this paper is about Risk Based Inspection (RBI) that is widely used in oil and gas industry. For prediction of cost and risk, machine learning is used to overcome the problems, comprises of artificial neural network and linear regression. © 2018 IEEE.