The fundamental purpose of insurance, whether of human being or of property, is protection against possible economic loss, economic loss being simply defined as the unintentional and permanent loss of something which has monetary value. Moreover, insurance is significant part of modern economy and it is huge source of employment. The main objective of this study was to identify the determinant factors of life insurance demand with different dimensions of life insurance in Bahir Dar city; the case of Ethiopian Insurance Corporation and Nyala Insurance Share Company. The researcher was employed quantitative research approach with explanatory research design to test explanatory variables family size, level of income, level of education, age, sex, premium, people’s attitude or perception, saving and premium, factors over the dependent variable (life insurance demand),in the case of Ethiopian insurance company and Nyala insurance company in Bahir Dar city. The researcher was employed multiple linear regressions using primary data source by questionnaire data collection technique. The researcher was collected 376 out of 384 distributed questionnaires from life insurance beneficiaries of Ethiopian insurance company and Nyala insurance company. The response rate was 97.92% among the respondents. The relationships proposed in the framework were tested using Pearson correlation from the result of the analysis it is concluded that age, premium, product variety, family size, saving and sex has positive and moderate relationship whereas level of awareness, and level of education has positive but weak relationship finally level of income has positive and strong relationship with dependent variable. Meanwhile under the regression result adjusted R-square was 63.27% and the R-square model fitness was scored 64.10%. In line with this the explanatory variables level of income, level of education, age, people’s attitude or perception, product variety and premium has positive and significant effect whereas family size has negative significant effect on the dependent variable i.e. life insurance demand in the 5% and 1% level of significance. Therefore, in order to achieve better practices in life insurance under the case study the researcher recommend that the government should support the sector as a whole and life insurance in particular in providing awareness.