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Background To explore the value of the neutrophil to lymphocyte ratio (NLR) combined with pancreatitis activity scoring system (PASS) in predicting severe acute pancreatitis patients.Methods The case data of SAP patients admitted to the General Hospital of Ningxia Medical University from January 2022 to January 2023 were retrospectively analyzed, and the patients were divided into the mild group and severe group according to the severity of the disease. The general situation, laboratory examination, prognosis and other indicators of the two groups were compared. Univariate analysis and Logistic regression were used to analyze the risk factors of severe SAP, and a receiver operating characteristic (ROC) curve was drawn to compare the predictive value of PASS score, NLR, PLR, NLR combined PASS score (PN score), and PLR combined PASS score (PP score) for severe patients with SAP.Results There were 203 cases of SAP in the mild group and 119 cases in the severe group. Respiratory rate, heart rate, blood pH, white blood cell count, absolute neutrophil value, relative neutrophil value, absolute lymphocyte value, NLR, PLR, calcium, potassium, fasting blood glucose, D-dimer, Internationally normalized ratio (INR), albumin, urea, lactate dehydrogenase, amylase, lipase, C-reactive protein (CRP), Procalcitonin (PCT) and Ranson scores were compared between the two groups, pancreatitis activity scoring system (PASS) score, Acute Physiology and Chronic Health Evaluation II (APACHEII) score, bedside index of severity in acute pancreatitis (BISAP) score, ICU admission rate, length of stay and cost were statistically different (P < 0.05), Logistic regression analysis showed that PASS score, lipase and amylase were independent risk factors for severe SAP patients. The ROC curve showed that the AUCs of NLR and PLR to predict the severity of SAP were 0.669 and 0.610, and the AUCs of PN score, PP score and PNP score to predict the severity of SAP were 0.970, 0.960 and 0.951, respectively.Conclusions PASS score combined with NLR and PLR can better predict the condition of SAP patients, and is expected to be better promoted and applied in the clinic.