This chapter explores the utility and limitations of clinical prediction rules (CPRs) in remote consultations, with a focus on family medicine and primary care. Family physicians are asked to deal with uncertainty in many situations and CPRs are statistical tools derived from large patient data sets that can support clinical decision-making by predicting disease risk, the potential benefits of interventions, and patient prognosis. In remote contexts, CPRs can be especially valuable where physical examinations are restricted, helping clinicians assess conditions ranging from cardiovascular diseases and mental health to infection risks. Examples like the Marburg Heart Score for coronary artery disease and the LOCH risk score for COVID-19 hospitalization that do not require an in-person visit are presented and discussed. While CPRs enhance diagnostic accuracy, predictive models may vary across different patient populations and settings. Therefore, they should complement rather than replace clinical judgment, and be updated and validated as needed to ensure relevance in evolving telehealth landscapes.