The current analysis analyzed the odds of casualties by road accidents. Hence, data were classified into tertiles for better research, and accident types were classified into five following the authority methodology: rollovers, crash, roadway departure, special accident, and car capsizing. Multi-logistic regression was employed for the data analysis. This research found that rollover was the most deadly accident, and the crash was the most probable to cause injuries.

It is not a secret that road accidents cause significant suffering. Those accidents can last from wounded to dead people, negatively impacting a country. A bunch of recent investigations tried to tie road accidents with the quality of roads. Therefore, in a country with a significant infrastructure gap, it is necessary to analyze the relationship between the different kinds of roads and the severity of car accidents. The current research examined such a relationship by employing the Multi logit regression. It was found that the significance of different car accidents will vary among the road types. Moreover, with the help of probability analysis, it was discovered that speeding, emergency services availability, and road security seemed to have a crucial impact on road accidents.