Potential applications are increasingly shown in the literature enabled by the advent of scaffolded DNA origami [1]. We employ a data-driven approach, applying machine learning to a curated a database collected from Nucleic Acid Origami literature. We expect to aid the design of well-formed nucleic acid origami through machine learning informed lab protocols and algorithm improved sequence design. This will lead to improved application of nucleic acid origami, with increased yield, scale and complexity. [1] Paul W. K. Rothemund. Folding DNA to create nanoscale shapes and patterns. Nature, 440(7082):297–302, March 2006.