Using large cohorts from published clinical trials involving more than 8,000 patients with multiple sclerosis, a probabilistic machine learning model reconstructs the transition probabilities from data-derived diseases statuses, showing patterns that suggest how progression to severe stages occur and potential inversion of the process.