Road traffic collisions (RTCs) represent a significant public health challenge, particularly in countries with elevated mortality rates from such incidents. In Libya, the scarcity of digitized RTC data hampers robust analysis and subsequent intervention strategies. This study aims to bridge this gap by meticulously transforming over 2,300 hard-copy RTC reports from the Ajdabiya Traffic Police Department archives into a structured electronic database. For this analysis, 1,255 rural freeway incidents were scrutinized using a Binary logit model (BLM) to ascertain determinants of injury severity. It was found that head-on collisions, elevated speeds, the use of private cars, and weekend incidents markedly increased the likelihood of severe injuries. Examination of investigative reports disclosed a significant deficiency in traffic safety awareness among enforcement personnel, coupled with suboptimal law enforcement. To augment road safety in Libya, the enforcement of traffic laws, speed regulation, and activation of emergency medical services are identified as primary interventions. Additionally, the establishment of an integrated, multi-source database is imperative to advance traffic safety research and policy development.