(1) Background: The study was aimed at a better understanding of the factors determining making a decision to become a potential bone marrow donor, in a Polish research sample; (2) Methods: The data was collected using a self-report questionnaire among persons who voluntarily participated in the study concerning donation, conducted on a sample of the Polish population via Internet. The study included 533 respondents (345 females and 188 males), aged 18–49. Relationships between the decision about registration as potential bone marrow donor and psycho-socio-demographic factors were estimated using the machine learning methods (binary logistic regression and classification & regression tree); (3) Results. The applied methods coherently emphasized the crucial role of personal experiences in making the decision about willingness for potential donation, f.e. familiarity with the potential donor. They also indicated religious issues and negative health state assessment as main decision-making destimulators; (4) Conclusions. The results of the study may contribute to an increase in the effectiveness of recruitment actions by more precise personalization of popularizing-recruitment actions addressed to the potential donors. It was found that selected machine learning methods are interesting set of analyses, increasing the prognostic accuracy and quality of the proposed model.