This paper accesses the availability of credit for women in Eritrea using a probit regression model. A woman as a variable is fitted into the probit model with other variables. The parameters in the model are estimated using the maximum likelihood approach over the ordinary least square because the dependent variable is a binary. For policy implications, the marginal effects of the explanatory variables are also derived. The result shows that gender and adoption of rain water collection technology had the greatest impacts on women access to credit followed by access to extension officer visit and number of children in the household. Women households had less to access credit facility due to collateral and social constraints, especially in the male-dominated agricultural businesses. Without serve as collateral, women are also cut off from access to credit, and without credit, they often cannot buy essential inputs to boost production. The study recommends that, Saving and Micro-credit program (SMCP) in Eritrea doing valuable work in improving women’s access to credit, the government should mobilize resources to coordinate among different stakeholders involved in development programs and the financial institutions to sustained and ensure women’s access to credit.