Current methods for the diagnosis of sepsis have insufficient precision, causing regular misdiagnoses. Microbiological tests can help diagnose sepsis but are usually too slow to have an impact on timely clinical-decision making. Neutrophils have high sensitivity to infections, yet measurements of neutrophil surface markers, genomic changes, and phenotype alterations have had only a marginal effect on sepsis diagnosis. Here, we report a microfluidic assay that measures the spontaneous motility of neutrophils in the context of plasma, in one droplet of blood. We measured the performance of the assay in two independent cohorts of critically ill patients suspected of sepsis. In the first cohort, we developed a machine-learning-based scoring system (sepsis score) that segregated patients with sepsis from those without sepsis. In the second cohort, we validated the sepsis score in a double-blinded, prospective case-control study. For the 42 patients across the two cohorts, the assay identified sepsis patients with 97% sensitivity and 98% specificity. The neutrophil assay could potentially be used to accurately diagnose and monitor sepsis in larger populations of at-risk patients.