The rapid advance in information and communication technologies has effectively facilitated the development and implementation of information systems (IS) projects in modern organizations for reorganizing their business processes and streamlining the provision of their products and services in today's dynamic environment. Such a development brings organizations with numerous benefits including increased automation of business processes, improved customer service, and timely provision of effective decision support. As a result, evaluating and selecting the most appropriate IS project for development and implementation from a pool of available IS projects becomes a critical decision to make in modern organizations. Evaluating and selecting appropriate IS projects for development in an organization, however, is complex and challenging. The complexity of the evaluation and selection process is due to the multi-dimensional nature of the decision making process, the conflicting nature of the multiple selection criteria, and the presence of subjectiveness and imprecision of the human decision making process. The challenging of the evaluation and selection comes from the need for making transparent and balanced decisions based on a comprehensive evaluation of all available IS projects in a timely manner. Much research has been done on the development of various approaches for evaluating and selecting IS projects, and numerous applications of those approaches for addressing real world IS project evaluation and selection problems have been reported in the literature. In general, existing approaches can be classified into (a) cost-benefit analysis based approaches, (b) utility based approaches, and (c) optimization oriented approaches. These approaches, however, are not totally satisfactory due to various shortcomings including (a) the inability to tackle the subjectiveness and imprecision of the selection process, (b) the failure to adequately handle the multi-dimensional nature of the problem, and (c) cognitively very demanding on the decision maker. To address these issues above, this research has developed three novel approaches for effectively solving the IS project evaluation and selection problem under uncertainty in an organization. The first approach is developed for helping the decision maker better model the subjectiveness and imprecision inherent in the decision-making process with the use of linguistic variables approximated by fuzzy numbers. The second approach is designed to reduce the cognitive demanding on the decision maker in the IS project evaluation and selection process with the introduction of fuzzy pairwise comparison. The third approach is formulated with respect to the use of intelligent decision support systems for facilitating the use of specific multi-criteria analysis approaches in relation to individual IS project evaluation and selection situations. The developed approaches have been applied for solving three IS project evaluation and selection problems in the real world settings. The results show that the three developed ap proaches are of practical significance for effectively and efficiently solving the IS project evaluation and selection problem due to (a) the simplicity and comprehensibility of the underlying concept, (b) the adequate handling of inherent uncertainty and imprecision, and (c) the ability to help the decision maker better understand the IS project selection problem and the implications of their decision behaviours.