<p>Due to the computational complexity of Generalized Type-3 Fuzzy Systems, there exist many research gaps to be solved to be able to apply this kind of systems in real-world applications. At the moment, most of the type-3 fuzzy papers in the state of the art are utilizing interval type-3 fuzzy systems, which are a simpler and reduced version of the full type-3 models. The objective of this paper is to build a full model of Generalized Type-3 Fuzzy Systems and Sets, for addressing the implementation gaps. For example, the paper proposes the concept of <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40815_2025_2092_Article_IEq1.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="13" /> </InlineMediaObject> <EquationSource Format="TEX">\(\upbeta \)</EquationSource> <EquationSource Format="MATHML"><math> <mi mathvariant="normal">β</mi> </math></EquationSource> </InlineEquation>-planes for modeling Generalized Type-3 Fuzzy Sets, the mathematical modeling of Generalized Type-3 Membership functions, Generalized Type-3 reduction and the architecture of Generalized Type-3 Mamdani Fuzzy Inference Systems. In addition, the paper includes a step-by-step graphical example of this kind of inference system for a better understanding of the concepts and some practical examples are presented with the objective of demonstrating the feasibility of implementing these kinds of systems in engineering or in other complex problems. Additionally, the paper presents a comparative analysis in terms of complexity to determine in which conditions the Generalized Type-3 Fuzzy Systems could be a good approach considering the computational effort required by these systems.</p>