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Background: Fertility is one of the important characteristics of population studies. The number of children ever born per woman has important implications for public health, economic, climate, and population structure. There are many literatures about fertility and factors which are significant effects on it. The aim of this article is modeling Children Ever Born (CEB), as an important factor affects fertility using Poisson regression.Methods: We collected 405 women 15-49 year-old by random stratified sampling and structured questionnaire in 2012. Statistical population are married women from Semnan province. Birth local, educational level, job status and type of marriage were considered as prpbalbe effective factors on CEB and their significancy was determined by Poisson regression.Findings: Among birth local, educational level, job status and type of marriage, only birth local and educational level had statistically significant effects on CEB (p< 0.001). Women who were born in rural area and had under diploma educational level had higher CEB than women who were born in urban area and had diploma or above educational levels.Conclusion: Since CEB is a count variable, it is recomanded to use Poisson regression instead of linear regression model. In this situation, Poisson regression is more realable than classical regression. Key Words: Fertility, Children Ever Born (CEB), Poisson Regression

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