Blood is very important for keeping humans alive. One of the biggest challenges facing blood banks is the difficulty in finding blood donors. So, blood bank systems should be effective in finding potential donors. In this project, we have proposed a knowledge-based system that in- creases the chance to find possible blood donors. Random Forest is the Machine Learning (ML) algorithm that will be used to develop a classifier to categorize people into two groups: peo- ple who are more likely to donate blood and people who are less likely to donate blood. The classification will be based on factors like people’s values, and their culture. These factors are influence people’s behaviors so, it will help knowing donors from non-donors. Our proposed system aims to improve the efficiency of blood bank systems and reduce costs by contacting potential donors rather than contacting someone who is not willing to donate.