With the rapid urbanization of the Chengdu Plain, the risk of periurban soils exposing to heavy metal pollution is aggravating gradually, however, so far no ready-made research method is handy to study quantitatively impact of socio-economic development on soil heavy metal pollution.An attempt was made to study internal relationships between Cd content in soil and its affecting factors related to the socio-conomy of the urbanization of the Chengdu Plain with the aid of the BP Artificial Neural Network, which was made up of one input layer of 12 inputs, one output layer and one hidden layer.The network fit extremely well with precision reaching 97.02%.This BP network model was used to predict Cd content in peri-urban soils, with results 84.19% in precision, which is obviously higher than 71.mer in predicting heavy metal pollution.Then the predicted data of each affecting factor in year 2005 and year 2010 were input into the network, and merged with the previous samples.The model was trained over again to renew the network weight values.Thus soil Cd content in each county in the Chengdu Plain in year 2005 and year 2010 was predicted55% of the traditional regression model, showing superiority of the for.