Improving the safety of cyclists, who are considered vulnerable road users, is essential. Implementing a warning system that alerts cyclists to nearby hazards is an effective method to improve their safety. Nevertheless, the literature needs a comprehensive and detailed review of cyclist warning systems. This paper presents a systematic review of existing studies about warning technologies and systems developed to improve cyclist safety, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (n = 78). Based on the review, it was found that the most used cyclist warning technologies were cameras with artificial intelligence (AI), ultrasonic sensors, lidar, and radar. Furthermore, there were some insights from the studies that conducted cycling experiments with the use of a warning system: (1) most participating cyclists responded positively to the warning technologies/systems, (2) most cyclists preferred auditory signals over visual or haptic signals as warning modalities, (3) warning technologies/systems influenced some cyclists’ behaviour during critical situations, such as early braking, faster reactions, increased focus, maintaining a safer distance, and temporarily reducing speed, and (4) only two studies tried to explore how warning systems affect crash risk. Future research should focus on developing warning systems that are compact, lightweight, and affordable. More studies are also needed to demonstrate the impact of the cyclist warning system on cyclists’ crash risk. This review identifies gaps in the current literature and offers a solid foundation for future studies to enhance cyclist safety.