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In this study, the nonlinear relationship between summer rainfall in the Red River Delta and the El Niño–Southern Oscillation (ENSO) was examined using observational station data and sea surface temperature anomalies in the Niño 3.4 region (ONI). First, the distribution characteristics of rainfall and sea surface temperature (SST) were analyzed based on the frequency of rainfall and temperature within specific ranges. Next, the relationship between the frequency of rainfall across different quantiles and SST was explored using polynomial regression. The results indicated that, during summer, months with negative rainfall anomalies occur more frequently than those with positive anomalies. However, extreme positive rainfall anomalies (>200 mm/month) tend to occur more often than extreme negative ones (<200 mm/tháng). Although the linear correlation between rainfall anomalies in the Red River Delta and ONI is weak, their nonlinear relationship could be captured by polynomial regression, yielding relatively high R² values ranging from 0.64 to 0.9. Specifically, for lower rainfall quantiles, regression models using ONI from April to September provide better fits, while for middle and upper quantiles, models based on ONI from May to October perform better.