This study aimed to investigate the clinical, electrophysiological characteristics and blood inflammatory markers in severe Guillain-Barré syndrome (GBS) and their correlation with short-term prognosis. Data from 95 patients with severe GBS were classified into two groups based on the Hughes functional grading scale (HFGS) on day 28: those with poor prognosis (>3) and those with prognosis (≤3). Clinical characteristics, nerve conduction studies and blood parameters were compared at admission between the two groups. Logistic regression analysis identified predictive factors for GBS, and receiver operating characteristic (ROC) curves were used to evaluate the predictive efficacy. A nomogram model combining these predictive factors was constructed and evaluated using ROC and calibration curves and Hosmer⁃Lemeshow goodness-of-fit test. The poor prognosis group exhibited bulbar paralysis and an elevated modified Erasmus GBS Outcome Score (mEGOS) (P < 0.05). Nerve conduction studies revealed increased numbers of inexcitable motor nerves (IMN) in the poor prognosis group. Blood analysis showed significantly elevated neutrophil-to-lymphocyte ratio (NLR) during acute disease stage (P < 0.05) compared with the good prognosis group. ROC curve analysis indicated that mEGOS, NLR value, IMN number, and their combination had area under the curve (AUC) values of 0.818, 0.757, 0.870, and 0.947, with sensitivities of 78.4 %, 76.5 %, 75.0 %, and 92.2 %, and specificities of 77.3 %, 77.3 %, 61.3 %, and 86.4 % respectively, for short-term prognosis prediction. The nomogram model demonstrated an area under the ROC curve of 0.990, reflecting good potential clinical effect. The calibration curve showed good agreement between actual observations and nomogram predictions. The findings indicate that early assessment of the occurrence of bulbar palsy, mEGOS, IMN numbers, and NLR value can predict poor prognosis, with their combination providing improved accuracy for short-term prognosis in patients with severe GBS.