The rapid rise in railroad transport across the world demands an improved service in form of safety, comfort, reliability, and cost-effectiveness. For the improvement of reliability, safety, and efficiency; sophisticated Condition Monitoring Systems (CMS) have become an important part of modern railway operations. CMS for railway vehicles involves techniques including model-based and signal-based techniques for the detection of faults. These techniques assist in preventing the system from any major failure. The core element of a CMS is the use of suitable algorithms to evaluate system behavior for achieving a solution to avoid accidents of railway vehicles. This paper attempts to compare and evaluate the existing state-of-the-art condition monitoring techniques applied for real-time monitoring of railway wheel-set dynamics. In addition, recommendations are presented for future research efforts in this area.