With increasing vehicle population, the need for techniques that ensure vehicle safety is felt much more nowadays. One of the critical functions of a vehicle is braking, which indicates why most vehicular safety systems, such as Anti-lock Braking Systems (ABS), Electronic Stability Control (ESC), and Roll-over prevention involve the brake system. ABS is an active safety technology used to ensure vehicle safety by preventing wheel lock up and reducing the stopping distance during severe braking. ABS algorithms fall under two broad categories. Firstly, Model Based Algorithms (MBAs) that typically involve control of the system using a physics-based model developed from first principles. Secondly, Rule Based Algorithms (RBAs) that are empirical, and based on a set of pre-defined thresholds for controlled parameters. RBAs are more prevalent in the commercial space due to their lower data requirement, while most laboratory research has focused on MBAs. One of the most popular MBAs applied to ABS is Sliding Mode Control (SMC) owing to its inherent robustness to parameter variations and external disturbances. SMC-based ABS has, thus, been a focal point of academic study and the corresponding techniques have evolved considerably owing to a vast amount of literature. However, this is not complemented by their application in commercial ABS solutions, possibly because MBAs use mathematical models and require information pertaining to vehicle and tire parameters, which are generally difficult to obtain in real-time. While various technical aspects are usually considered for ABS evaluation, an important literature gap is the absence of any index/parameter that accounted for the implementability of a proposed system, which becomes important when considering its commercial viability and scaleability. The proposed research involves the development of a framework to evaluate rule-based and model-based ABS algorithms of heavy road vehicles, considering both technical and commercial aspects. The proposed framework is expected to quantify an ABSs performance, while also indicating the extent to which it is tractable for commercial implementation.