Maternal mortality causes loss of lives among others. In this work, we obtain the maternal mortality rates (MMR) in Nigeria, identify some fitted distributions to MMR, and determine which distribution best fits the data. The statistical methodology adopted in this research work is mainly probability distribution modeling approach. Method: A comprehensive exploratory data analysis was carried out on maternal mortality data collected and the MMR was obtained. The result shows that the rate was very high in 2012 and 2011 but a low rate was observed in 2014 indicating that some measures were put in place to control the situation and a sudden increase in 2015 and 2016 was also noticed suggesting a failure in some of the measures put in place in the previous years. Discussion: Two parameters gamma distribution, lognormal, Weibull, and exponential distributions were fitted for MMR. Both Bayesian information criterion (BIC) and Akaike information criterion (AIC) selection criteria were adopted in selecting the most fitted distribution. The AICs for gamma, lognormal, Weibull, and exponential distributions fitted for MMR were 1339.396, 1363.899, 1340.161, and 370.5244, respectively. Furthermore, the BICs for gamma, lognormal, Weibull and exponential distributions fitted for MMR were 1344.971, 1369.474, 1345.736, and 373.3119, respectively. Conclusion: It can be observed that exponential distribution has the least AIC (370.5244) and least BIC (373.3119); therefore, it is the most fitted distribution of all the distributions fitted for MMR. The estimate (standard error) of exponential distribution on MMR is 0.5853 indicating the fitness of the distribution being the one with the least standard error. In conclusion, the model obtained in this study can be used to study MMR in Nigeria to achieve a better economy and thus brings about local and national development. Future research can be extended to statistical analysis of the causes of maternal mortality
