Company executives are under increasing pressure to proactively evaluate the benefits of the huge amounts of investment into intellectual property (IP). The main goal of this paper is to propose a Dynamic Bayesian Network as a tool for modeling the forecast of the distribution of Research and Development (R&D) investment efficiency towards the strategic management of IP. Dynamic Bayesian Network provides a framework for handling the uncertainties and impression in the qualitative and quantitative data that impact the effectiveness and efficiency of investments on R&D. This paper specifies the process of creating the graphical representation using impactful variables, specifying numerical link between the variables and drawing inference from the network.