The scalability of data mining techniques is very important due to the rapid growth in the size of databases.  Usage of decision tree classifiers has become an effective classification model.  The main objective of this research is to study the existing Scalable Decision Tree Classifiers (SDTC’s) and analyze them to find the best algorithm.  Our aim is also to design a new SDTC algorithm and compare it analytically with the existing ones.