Point of care testing (POCT) allows, among others, for efficient care of patients presenting with acute problems to primary care physicians. A combination of clinical information and laboratory results enables physicians to obtain posttest probabilities for the presence or absence of a specific disease. In order to rule in or rule out a disease, the physician has to know both the pretest probability for a disease in a patient as well as the analytical and diagnostic characteristics of the employed test. Pretest probability can be assessed by scores or by personal judgment of the experienced clinician. This article presents the basics of the Bayes theorem together with its clinical applications in acute scenarios in primary health care. These scenarios comprise the use of D-Dimer testing in ruling out venous thromboembolism, rapid testing of group A streptococci in the setting of acute pharyngitis, troponin testing in patients with thoracic pain, c-reactive protein (CRP) testing in patients presenting with acute cough and fever, as well as urine dipstick testing in suspected urinary tract infection. These examples illustrate, that risk stratification before conducting laboratory analysis is of utmost importance in order to obtain valid results for ruling in or ruling out diseases in POCT-settings.