When a cash flow analysis is performed, the most common problem found by an analyst is the uncertainty of the information used in the model. Practically, the probabilistic cash flow model is usually recommended when the high uncertainty of data persists. Unfortunately, it requires a great deal of information and time to set up a good probability distribution. For ease of analysis, the uncertainty of the data is usually ignored and a deterministic model is applied. Although efficient, this technique may lead to an ineffective analysis. Fuzzy sets theory, proposed by Zadeh, offers another mathematical tool to deal with the uncertainty of data. It is believed that the resulting analysis is more useful and accurate if the uncertain data is represented by fuzzy numbers, and is properly analyzed through the use of fuzzy sets theory and techniques. In this study, the fuzzy total cash flow model is proposed by assuming some components in the total cash flow model to be fuzzy numbers. A single project evaluation technique is also provided.