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Additive Manufacturing (AM) is currently considered as the spark of a new industrial revolution, due to its versatility in creating 3D structures of unprecedented design freedom and geometric complexity in comparison with conventional manufacturing techniques. Due to differences in AM technologies the final fabricated part can vary, sometimes dramatically, from the originally designed one, therefore raising issues regarding dimensional accuracy, surface finish, mechanical properties, functional and geometrical requirements. Various research efforts have articulated the correlation between AM technologies and design process, in terms of integrating specific design rules or guidelines pertinent to model complexity, design potentials and constraints of each AM process.

In this work we propose a novel approach to assessing the quality and ability of a 3D model to be printed successfully (a.k.a printability) on a specific AM machine. This is utilized by taking into consideration the model mesh complexity and certain design features. A $printability$ $score$ is derived for a model in reference to a specific 3D printing technology, expressing the probability of obtaining a robust and accurate end result for 3D printing on a specific AM machine. The printability score can be used either to determine which 3D technology is more suitable for manufacturing a specific model or as a guide to redesigning the model to ensure printability. We verify this framework by conducting 3D printing experiments for benchmark models which are printed on three AM machines employing different technologies: Fused Deposition Modeling (FDM), Binder Jetting (3DP), and Material Jetting (Polyjet).