Blank C, et al. - Researchers undertook a retrospective study of a 2-year single-center cohort of 1,052 women undergoing in vitro fertilization (IVF) or intracytoplasmatic sperm injection (ICSI) treated with the use of single-embryo transfer (SET) of blastocyst-stage embryos, to develop a random forest model (RFM) predicting implantation potential of a transferred embryo and compare it with a multivariate logistic regression model (MvLRM). In this work, the RFM approach and the MvLRM yielded, respectively, sensitivities of 0.84 ± 0.07 and 0.66 ± 0.08 and specificities of 0.48 ± 0.07 and 0.58 ± 0.08. Outcomes suggest that the use of an RFM approach may significantly enhance the performance to predict ongoing implantation when compared with MvLRM.