BACKGROUND AND OBJECTIVES: Neurologic deterioration frequently occurs during the acute phase of isolated pontine infarction (IPI). However, the factors that predict early neurologic deterioration (END) are not well understood. The purpose of this study is to identify and analyze the predictors of END in individuals with IPI. METHODS: One hundred and fifty-three patients diagnosed with acute IPI were included in this retrospective study, including 41 individuals in the END group and 112 in the non-END group. Demographic characteristics, clinical data, and imaging features were collected and compared. Logistic regression analysis was used to identify independent predictors of END in patients with IPI, and a receiver operating characteristic (ROC) curve was constructed to assess model performance. RESULTS: Univariate analysis demonstrated significant differences between the two groups regarding diabetes mellitus, National Institute of Health Stroke Scale (NIHSS) score at admission, etiological classification, and infarct area, with P values less than 0.05. Multivariate binary logistic regression analysis revealed that the NIHSS score at admission and the infarct size were independent predictors of END. The combined ROC analysis of the NIHSS score at admission and the infarct area for predicting END showed a sensitivity of 85.4%, specificity of 83.0%, and an area under the curve of 0.887. CONCLUSIONS: Basilar artery branch disease is the primary cause of END observed in IPI. Both the NIHSS score at admission and the size of the infarct serve as significant predictors for END in IPI, and the combination of two factors provides value in predicting END and outcomes of IPI patients. Early prediction of END also can guide treatment strategies, aimed at improving patient prognosis.