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The leaf area index (LAI) and specific leaf area (SLA) simulation model of processing tomato with drip irrigation were developed based on the accumulated physiological development time after emergence (PDT). Then a simulation of leaf area, dry matter production and accumulation of processing tomato with drip irrigation was developed based on physiological and ecological processes of photosynthesis and dry matter production simulation model. The results showed that when using the model based on PDT, the coefficient of determination (R2), root mean squared error (RMSE) and modelling efficiency indexes (ME) between simulated and measured leaf area index based on the 1∶1 line were 0.926 5, 12.87% and 0.972 4, respectively. However, when using the model based on SLA, the R2, RMSE and ME between simulated and measured LAI based on the 1∶1 line were 0.675 8, 42.24%, and 0.712 4, respectively. When using the model based on PDT, the R2, RMSE and ME between simulated and measured aboveground dry matter weight based on the 1∶1 line were 0.990 3, 11.91% and 0.990 1, respectively. However, when using the model based on SLA, the R2, RMSE and ME between simulated and measured aboveground dry matter weight based on the 1∶1 line were 0.895 6, 31.29% and 0.750 4, respectively. Compared with the SLA method, PDT method to improve the processing tomato leaf area index prediction accuracy while also improving the prediction accuracy of the aboveground dry matter weight.