Information Technology (IT) is a service to provide an organization with a tool to improve transaction processing, employee productivity and additionally to enhance day-to-day business processes. Also IT is looked as an aid to develop intellectual capital such as decision-making power and to add value to the organization products and services for which it has to bear a cost. IT implementation and support cost comprises one of the most expensive elements in an organization’s shared services or support function [1]. The decision on investment in IT is generally taken by top management decision makers who often fail to integrate their concerns with the expected outcome of an investment in IT. The problem is aggravated by the fact that the return on IT investment, that is the value addition to the organization, is often estimated by some qualitative assessments and business decision based on educated guess. Quantitative evaluation of IT investment is difficult to achieve because assessing IT investment is not restricted to a strict quantification of clearly identifiable costs and benefits, but a more balanced approach combining hard metrics and mission-critical intangibles. But in reality, can the standard economic models (e.g. NPV or the IRR method) be taken up for the evaluating the worth of an IT investment? Investments in Information Technology do exhibit some different characteristics to many other business investments. These differences include the fact that IT investment opportunities frequently evolve, not only over long periods of time, but during the relatively short periods while the information system is actually being developed. This means that the final investment is sometimes not known in detail at the outset of the work. Added to this, any organization undergoes simultaneous investments in other branches of business and consequently the part of return in the business due to IT investment cannot be specifically assimilated. As because it is difficult to ensure the exact association of the return on investment in IT with the expenditure incurred in IT with standard economic models, this paper attempts to present a non-conventional approach, the fuzzy logic principle, to achieve the objective. This is based on the empirical data available on IT investment in an organization (“Input Space” of the fuzzy domain) and probable benefit areas (“Output Space”). The objective is to map the input space to the output space. For this the membership functions of eachelement of the input and output space on the available data set is defined. Then we define a set of fuzzy rules, which shows the relationship between the elements of input and output space, based mostly on educated guess. As a final step the analysis can be carried out through the defuzzification process; which in a crisp manner determines how much moderation should be made in the Input space elements (IT investment areas in this case) to have a desired outcome in the Output space elements (benefit areas of business). Keywords: Information Technology, NPV, IRR, Fuzzy logic, Input Space, Output Space, membership function, fuzzy rules, defuzzification.