Introduction The clinical presentation of coronavirus disease 2019 (COVID-19) overlaps with many other common cold and influenza viruses. Identifying patients with a higher probability of infection becomes crucial in settings with limited access to testing. We developed a prediction instrument to assess the likelihood of a positive polymerase chain reaction (PCR) test, based solely on clinical variables that can be determined within the time frame of an emergency department (ED) patient encounter. Methods We derived and prospectively validated a model to predict SARS-CoV-2 PCR positivity in patients visiting the ED with symptoms consistent with the disease. Results Our model was based on 617 ED visits. In the derivation cohort, the median age was 36 years, 43% were men, and 9% had a positive result. The median time to testing from the onset of initial symptoms was four days (interquartile range [IQR]: 2–5 days, range 0–23 days), and 91% of all patients were discharged home. The final model based on a multivariable logistic regression included a history of close contact (adjusted odds ratio [AOR] 2.47, 95% confidence interval [CI], 1.29–4.7); fever (AOR 3.63, 95% CI, 1.931–6.85); anosmia or dysgeusia (AOR 9.7, 95% CI, 2.72–34.5); headache (AOR 1.95, 95% CI, 1.06–3.58), myalgia (AOR 2.6, 95% CI, 1.39–4.89); and dry cough (AOR 1.93, 95% CI, 1.02–3.64). The area under the curve (AUC) from the derivation cohort was 0.79 (95% CI, 0.73–0.85) and AUC 0.7 (95% CI, 0.61–0.75) in the validation cohort (N = 379). Conclusion We developed and validated a clinical tool to predict SARS-CoV-2 PCR positivity in patients presenting to the ED to assist with patient disposition in environments where COVID-19 tests or timely results are not readily available.