Property price and transaction activities may contain many factors. Data mining for property research provides a feasible way to analyze the trend and to understand the underlying influential factors. This paper addresses the issues and techniques on experiences in data mining for Macau property market. The original data for property price and factors are obtained as a multi-attribute dataset from the Statistics and Census Service of Macao SAR Government. The challenge is to apply different data mining methods and algorithms which include SVM, Neural Network, CandR Tree, Weka, SPSS, Multilayer Perception Model in order to identify hidden knowledge.