Many organizations seek statistical modelling facilitated by data analytics technologies for determining the prediction models associated with M\&A (Merger and Acquisition). By combining these data analytics tool alongside with data collection approac...
Many organizations seek statistical modelling facilitated by data analytics technologies for determining the prediction models associated with M\&A (Merger and Acquisition). By combining these data analytics tool alongside with data collection approaches aids organizations towards M\&A decision making, followed by achieving profitable insights as well. It promotes for better visibility, overall improvements and effective negotiation strategies for post-M\&A integration. This paper explores on the impact of pre and post integration of M\&A in a standard organizational setting via devising a suitable statistical model via employing techniques such as Naïve Bayes, K-nearest neighbour (KNN), and Decision Tree \& Support Vector Machine (SVM).