Bicycles are employed as means of transportation across various age groups, from young students to the elderly, for work, education, health, and leisure trips. Despite not achieving high speeds, bicyclists remain vulnerable to severe and even fatal injuries when they are involved in traffic accidents. Although the rising awareness of ecological issues and traffic law enforcement mean that cyclists are increasingly susceptible to road traffic crashes and injuries. Injuries resulting from a traffic accident involving cyclists can show distinct and specific characteristics depending on the manner of occurrence. The aim of this study is to provide a systematic review of the literature on injuries sustained in cyclists involved in road accidents describing and analysing elements useful for forensic assessment. The literature search was performed using PubMed, Scopus, and Web of Science from January 1970 to March 2023. Eligible studies have investigated issues of interest to forensic medicine about traffic accidents involving bicycles. A total of 128 studies satisfied the inclusion criteria and were categorized and analyzed according to the anatomical regions of the body affected (head, neck, thoraco-abdominal, and limb injuries), and the assessment of lesions in reconstruction of the bicycle accident was examined and discussed. This review highlights that injuries resulting from a traffic accident involving cyclists can show distinct and specific characteristics depending on the manner of occurrence and the energy levels involved in the crash. The assessment of injuries offers valuable insights that integrated with circumstantial and engineering data perform the reconstruction of accident dynamics. •Bicycle riders are susceptible to high and low-energy impacts, each associated with distinct fatal injury patterns.•The unique injury patterns found in bike riders can relate to helmet usage or not and to bike structural components.•Features of the injuries help in reconstructing the accident dynamics, combined with circumstantial and engineering data.