An efficient Artificial Neural Networks(ANN) method was developed to predict the microbial growth in beef. The targeted environmental factors were: temperature(-2, 0, 5 and 10°C) and Modified Atmosphere Packaging(MAP) air component(65% O₂, 35%CO₂ and 80% O₂, 20%CO₂). The ANN model used the three-vector model and was further developed into a four-vector model(bacterial species was imported into the model as an extra vector) which can predict all microbial growth in the single model. It turned out that both the ANN models were closely matching to the modeling datasets. And the disparity between two models was also not significant in testing datasets. This indicated that the more variables introduced did not affect the accuracy of ANN model. Using this model, the bacterial counts and remaining shelf-time of beef can be rapidly predicted by filling the air component and temperature into input layer.