Abstract: Knowledge transfer impacts the performance of any firm and its adaptability to the environment and associated change. Various knowledge management models capture the process of knowledge transfer and also help in explaining the efficacy of the transfer process. Artificial Neural Networks (ANN) can help to simulate and predict the knowledge transfer outcomes in the same way as the human brain perceives and interprets information to provide any learning outcome. However ANN has various algorithms each of which is an independent direction. This study discusses the direct application of Artificial Neural Network (ANN) framework to execute knowledge transfer using multiple ANN algorithm’s and perform efficacy and ability determination to estimate the appropriateness of the knowledge transfer method. Virtual reality based simulated environment is used as a vehicle to make the knowledge transfer and the ability of subjects of various categories to entrain on warehousing management domains is realized. The ANN applies to prediction of the knowledge level of the trained subjects initially by pre-training the ANN through multiple algorithms and then finding the closeness of the outcomes predicted through this network using multiple algorithms to the real data which is gauged through real examination of the trained subjects.