Crop modeling is a powerful tool for predicting yield and water productivity. The aim of the study was to calibrate and validate the AquaCrop model for tomato under staged deficit drip irrigation in Ethiopia. The AquaCrop model was calibrated and validated by using the observed data of canopy cover, biomass, dry yield, and soil water content. The results showed that the model was accurate in predicting canopy cover, biomass, and dry yield under different water levels. The overall performance in simulating canopy cover of AquaCrop, biomass, and soil water content showed a good match between measured and simulated data. The calibration results indicated good performance on canopy cover with 0.96 ≤ r ≤ 1.00, 2.9% ≤ RMSE ≤ 8.0%, 7.5% ≤ CV (RMSE) ≤ 21.1%, 0.91 ≤ EF ≤ 0.99, and 0.98 ≤ d ≤ 1.00. On biomass, the model calibration values were 0.99 ≤ r ≤ 1.00, 0.3 t/ha ≤ RMSE ≤ 0.8 t/ha, 8.3% ≤ CV (RMSE) ≤ 25.2%, 0.92 ≤ EF ≤ 0.99, and 0.98 ≤ d ≤ 1.00. Soil water content displayed poor performance on calibration, with performance values of 0.54 ≤ r ≤ 0.82, 3.6 mm ≤ RMSE ≤ 24.4 mm, 1.30% ≤ CV (RMSE) ≤ 9.00%, −4.18 ≤ EF ≤ 0.00, and 0.66 ≤ d ≤ 0.81. The validation results demonstrated that the model performed well on canopy cover with 0.96 ≤ r ≤ 1.00, 3.1% ≤ RMSE ≤ 7.7%, 8.2% ≤ CV (RMSE) ≤ 20.8%, EF ≥ 0.91, and d ≥ 0.9. The model validation correctly predicted biomass with r ≥ 0.98, 0.3 t/ha ≤ RMSE ≤ 0.7 t/ha, 8.9% ≤ CV (RMSE) ≤ 21.8%, EF ≥ 0.94, and d ≥ 0.98. The model validation poorly performed in forecasting soil water content, 0.20 ≤ r ≤ 0.80, 10.2 t/ha ≤ RMSE ≤ 24.0 t/ha, 3.5% ≤ CV (RMSE) ≤ 9.0%, −22.76 ≤ EF ≤ 0.63, and 0.40 ≤ d ≤ 0.87. The AquaCrop model is easy to use, requires less input data, and has high simulation accuracy, making it a useful tool for predicting crop yields and water productivity under staged deficit irrigation in areas with limited data.