The aim of this research is to evaluate digital interventions aimed at preventing falls among individuals aged 65 and older. The methodology employed involves a literature review assessing the effectiveness of various technologies in reducing fall risks, as well as identifying the strengths and weaknesses of each approach. The study includes elderly participants using digital technology or interventions compared to a control group receiving standard care or no intervention. Outcomes considered include reduced fall risk, fall incidents, or severity of fall-related injuries. Studies meeting inclusion criteria encompass experimental designs (randomized controlled trials, controlled trials) or observational studies with adequate controls, available in English. PubMed, Scopus, and IEEE Xplore databases were utilized up to June 19, 2024, with additional reference searches. Research findings indicate that out of 608 identified articles, 10 studies met inclusion criteria following screening processes. These studies utilized a variety of technologies such as mobile applications, virtual reality (VR), augmented reality (AR), machine learning, and robotics. Conducted in various countries, these studies demonstrate diverse applications; for instance, UK studies used mobile apps and 3D games for fall awareness, Chinese studies employed VR for rehabilitation, and German studies explored robotics for fall prevention. The research concludes by highlighting the potential of technologies like VR, AR, machine learning, and robotics in reducing fall risks among the elderly, thereby enhancing healthcare practices and quality of life. Keywords: Elderly, Falls Risk, Prevention, Technology