Additive manufacturing (AM) was introduced the 1980’s for rapid prototyping (RP) purposes but now AM provides complementary techniques to conventional manufacturing processes and offers advantages when components can be exacting, impossible, and too costly to be produced by conventional methods due to complex structures and geometric configurations, which require tailored designs. They are also often mass-customized components, with custom-made properties and low volume production requirements making AM the ‘technology of choice’ since its added-value aspects cannot be achieved by any other manufacturing technologies. These advancements in manufacturing, demand standardized fact-based decision support systems (DSSs), to support AM practitioners in their task selecting the most suitable techniques for given applications. Hence, this paper aims to increase the understanding of what – of how – DSSs are used in selecting and utilizing AM in various applications. This paper’s core message, considering practical implications, is to guide and support AM researchers with an overview of the DSSs for AM landscape. This paper presents and compares different models and tools classified within four categories used as DSS for AM and identifies their advantages and disadvantages by conducting a 3-step systematic literature review (SLR). A total of 388 literatures were initially retrieved, and according to an inclusion criteria analysis, the literatures were evaluated. This is the first SLR emphasizing and synthesizing obtainable literatures on AM DSS. Until now, this topic has acquired narrow exploration; however, the authors believe it is of rapidly growing importance to both scientists and practitioners.