A study was conducted to Statistical Analysis for Identification of Motor Vehicle Crash rnBlack Spots and Low Cost Improvements on the road from Addis Ababa to Debre rnBirhan. The research was conducted exhausting both historically recorded crash data rnand Predictive Empirical Bayesian statistical methods of analysis for identifying and rnprioritizing black spot segments. rnConsistent with results of black spot, the Upper Control Limit through Crash Rate rn(using Dangerous Factor, DF), Crash Score and Mixed Crash Frequency-Crash Rate rnstatistical methods were simultaneously applied and used to rank the most probable rnhazardous road segments through crash consequence types. rnThe predictive Empirical Bayesian method of statistical analysis was further used to rnidentify black spots which combine the observed actual number of Crash Frequency with rnthe predicted number of Crash Frequency. Then subsequently, the excess number of rnCrash Frequency was used to identify and rank segments. rnThe total number of Motor Vehicle Crashes reported was 587 within 2012/13-2015/16 rnperiod of study years, but some crashes contributed for more than one fatal, serious, slight rnand property damage consequences. Hence, based on the crash severity results, there were rn160 fatal, 254 serious injuries, 330 slight injuries and 488 property damages obtained rnfrom police recorded archive booklet files resulted for a total of 1,232 consequences. rnAccordingly, 20 segments among the 108 segments were identified as black spots. rnEstablished on the results, for six segments low cost improvements were recommended.