A statistical model for simulating flood inundation in Tuvalu is developed in this study. The model is based on the ma- jor regional inundation factors - spring tides and warm-water mass, integrated with the digital elevation. Nineteen years of sea level data from tide gauge and satellite altimetry are analyzed to predict regional flooding. Harmonic analysis is used in analyzing tidal variations to determine the major astronomical tidal constituent harmonic constants. Tidal variation prediction can be performed with these harmonic constants. The empirical mode decomposition (EMD) method is then applied to the sea level data derived from altimetry for extracting warm-water mass variation. Ninety percent of sea level data points are used for analysis, and the remaining 10% are used for testing the prediction accuracy. The sea level data derived from along-track satellite altimeter near Tuvalu is decomposed into eight modes and one local trend using the EMD method. The EMD mode periods found by fast Fourier transform (FFT) include monthly, intra-seasonally, half-yearly, yearly, bi-annually, and inter- annually oscillations. We apply these periods to harmonic analysis to predict the variations in warm-water mass. The sea level tide and warm-water mass combination predictions are compared to field measurements. The results show that the correlation coefficient is 0.988 with a root-mean-square error (RMSE) of 7.6 cm.