Improvement in computing technology has made it possible to examine social information that cannot previously be captured, processed and analysed. New analytical techniques of machine learning can be used in property research. This study is an exploratory attempt to use a machine learning algorithm in estimating housing prices, and then compare their results. Our study has shown that advanced machine learning algorithms like Linear Regression are promising tools for property researchers to use in housing price predictions. However, we must be cautious that these machine learning tools also have their own limitations. There are often many potential features for researchers to choose and include in the models so that a very careful feature selection is essential. Thus, with the help of data analytics, machine learning, and growing technology we can solve innumerable, complex day to day real life problems may it be price prediction, image recognition, early identification of diseases, and so on.