In this study, we evaluated the diagnostic value of symptoms of chronic polyneuropathy and to construct and validate a simple questionnaire that can help diagnose chronic polyneuropathy. In a multi-step procedure, we initially compiled a 12-item questionnaire concerning polyneuropathy symptoms. The questionnaire was completed by 117 polyneuropathy patients and 188 controls (headache, transient ischemic attack, multiple sclerosis). First, we calculated sensitivity, specificity and likelihood ratios of each symptom. Next, we used multi-variable logistic regression to create a model that could discriminate patients from controls, using only the most informative symptoms and their frequency of occurrence. Based on the regression coefficients, we developed a simple scoring system (Erasmus Polyneuropathy Symptom Score, E-PSS), which was externally validated in 140 cases with chronic idiopathic axonal polyneuropathy and 96 controls without polyneuropathy. We assessed performance with discrimination (area under the curve, AUC) and calibration analyses. Numb and tingling feet were most frequently reported by polyneuropathy patients and had the highest sensitivity. Walking on cotton wool and allodynia had the highest specificity. Logistic regression yielded a model that contained these four symptoms, complemented with balance problems and tingling hands. Based on this analysis, the E-PSS was created, ranging from 0 to 14. The E-PSS had a good performance (AUC = 0.92) in the derivation set and proved to be valid in the external population (AUC = 0.95). In conclusion, the Erasmus Polyneuropathy Symptom Score (E-PSS) is a simple, validated six-item score that takes the presence and frequency of six different symptoms into account and it may be a helpful tool to screen individuals for the presence of chronic polyneuropathy. © 2019 Peripheral Nerve Society.