This study utilizes Poisson regression to examine the total number of children ever born for all the surveyed women in Manipur, using data from the NFHS-5. Poisson regression is well-suited for modeling count data, such as fertility outcomes, due to its ability to handle discrete, non-negative variables. The model incorporates robust standard errors to deal with violations of the assumptions typically associated with Poisson models, such as under or over dispersion and heteroscedasticity in the residuals. Findings indicate that lower levels of education, age at first child, and limited health literacy are some of the significant predictors of higher birth rates. Furthermore, women from specific religious communities and economically disadvantaged backgrounds are likely to have more children, probably due to restricted access to family planning resources and healthcare services. These findings highlight the value for targeted policy interventions that prioritize improving women’s educational opportunities and health literacy. Such strategies are essential for effectively managing fertility rates in Manipur and are in line with national sustainable development goals focused on health and education improvements.