A thorough accident modeling effort was conducted to look into the extent of injuries suffered by e-bike riders. The reason this model was chosen—a generalized ordered logit model—was its ability to capture the ordinal nature of injury severity while preserving inter-data variability. Numerous markers have been identified that are associated with the degree of injuries incurred by e-cyclists. These variables include the following: the e-cyclist was older; the vehicle involved was large; the e-cyclist was at fault; the e-cyclist turned left; the e-cyclist crossed the road; the driver turned right; the incident occurred in an industrial region; it was a weekday; and there was a tree separation. The modeling results are used to propose safety countermeasures and interventions, including creating safety campaigns, improving geometric design and traffic control in low-developed areas, curve roads, and signalized intersections, and creating educational programs for particular age groups (e.g., older e-bikers, female e-bikers, and inexperienced drivers). In addition, a few intriguing research topics have been proposed, like examining the mechanism of an e-bike head-on collision, the mechanism of a collision involving e-bikers, motorcycles, and heavy trucks, and the safety effects of different separation treatments on the severity of injuries sustained by e-cyclists from both a kinematic and physics perspective.