Corrosion under insulation is one of the most important issues in the petroleum industry. Ordinarily, in order to check the corrosion, inspectors remove the insulation of pipelines to measure the level of corrosion on each section of pipelines. This procedure may take weeks for a site which distinctly affects the financial aspect of oil and gas companies due to the pause production of its high-value products; therefore, in most cases, inspectors spot-check pipeline corrosion based on their experience. However, because the environments on sites are various, experience-based inspection may not be suitable for every site. On the other hand, even though inspectors want to access more data for better understanding of the site before the site trip, historical data sometimes are lost or scattered which leads to a hard situation for preparation of corrosion inspection. This paper utilises passive RFID sensors, which are smart sensing technologies, to collect site data and then integrate them into a Building Information Modeling (BIM) system. A uniform corrosion model is also adapted from the theories of corrosion to leverage both sensor data and BIM elements' properties. They serve as inputs to calculate the corrosion rate which is the key value of corrosion prediction. Then, the corrosion prediction results are colour-coded on a BIM model which helps inspectors intuitively understand the prediction and prepare for the site inspection. In result, the proposed research could provide a novel approach for corrosion management under insulation. •Integrate BIM and sensors for corrosion prediction and visualisation.•A mathematical model has been developed for corrosion prediction.•A prototype has been developed to validate the efficiency of the proposed approach.