Our research is aimed at predicting air quality.The data is obtained from examining 31 monitoring stations which were distributed to 31 grid squares over some locations in Xiamem located in south east coast of China.6 air pollutants i.e.Sulphur(iv)oxide,Nitrogen(II)oxide,Carbon(II)oxide,Titanium sublimation pump,and Dust fall were monitored by the different stations.Through step wise discriminant analysis only Sulphur(iv)oxide Nitrogen(iv)oxide and Dust fall were selected to avoid the excessive calculation in modeling process. The major source of air pollution giving rise to the pollutants included industrial coal consumption,population density,Traffic flow and shopping density.There were other sources but they were however rejected on various grounds such us inability to be quantified during modeling.Significantly low correlation between the source of pollutant and the quantity of pollutant in the air among other reasons. The method used to analyze and develop the models is the step wise cluster analysis.To facilitate the computation R based statistical soft ware package was used. The computation and analysis yielded the tree and map which at an a level of significance,could predict the pollutant given a set of independent variables(source of pollution) Eventually this article will show the impact of the various sources of pollution and the pollutants to the general level.