<p>This research introduces a Fuzzy Analytical Hierarchy Process-based Additive Manufacturing Complexity Index (AMCI-VAT) that provides the ability to assess and reduce design complexity in the context of VAT photopolymerization additive manufacturing. The framework proposed utilizes hierarchical modeling, fuzzy logic, and expert judgments to describe the complexity of a part in comprehensive terms against the dimensions of geometric characteristics, feature complexity, machine configurations, and process parameters. The validation of the proposed method resulted in significant statistical results, including Cronbach’s α = 0.847 and R2 = 0.923 predicting build time. These results and five industrial case studies demonstrated that AMCI-VAT is a reliable prediction tool that achieves up to 31% cost savings and 28% build-time savings from design optimization. The application of AMCI-VAT with two-dimensional metrics for complexity was able to predict accuracy that saw an increase of 23% over geometrical or two-dimensional metrics alone. Integrating AMCI-VAT with a real-time design recommender system can provide a feasible opportunity to create contextual or actionable live feedback within CAD environments, achieving an average complexity reduction of 34% in tested components. The proposed framework provides a comprehensible and consistent complexity assessment method that acts as an aid for decision-making in early-stage design and creates a facilitating instrument for optimizing manufacturability through a reliable intensity index.</p>