The placenta is key for any successful pregnancy. Deviations from the normal dynamic maturation throughout gestation are closely linked to major pregnancy complications. Automatic segmentation and age prediction based on a 30sec MRI T2* scan is enabled and evaluated in >100 pregnancies. High abnormality scores correlate with low birth weight, premature birth and histopathological findings. Retrospective application on a different cohort imaged at 1.5T illustrates the ability for direct clinical translation. The proposed machine-learning pipeline runs in close to real-time and, deployed in clinical settings, has the potential to become a cornerstone of diagnosis and intervention of placental insufficiency.