Maintenance of road infrastructure assets is integral to providing a safe environment for road users. The performance of lane marking material is vulnerable to deterioration due to factors including traffic volume, lane marking material and pavement degradation. The aim of this research was to develop a systematic method of assessing and classifying lane marking durability performance i.e. the level of material wear, through analysis of Mobile Laser Scanning point cloud data and to compare its effectiveness against current visual assessment procedures. The extraction of lane marking point cloud data was undertaken using the intensity values of the lane marking material and the percentage of material wear was subsequently calculated. A Defect Classification System was developed with input from industry experts and allocated to the percentage of wear results. This provided georeferenced durability performance defect severity results along the extracted section of lane marking point cloud data, for use by Infrastructure Asset Managers when targeting the remediation of lane marking assets.