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[Display omitted] • The 3D printing effect and baking quality of 3D printed bread were evaluated. • The prediction model was based on Partial least squares regression analysis. • The 3D printing properties were predicated using rheo-fermentation models. • Simultaneous acquisition of 3D printing and post-processing properties was possible. The rheological properties of dough closely correlate to a dough's ability to be three-dimensionally (3D) printed, but only weakly characterize its fermentation and baking process. This study aimed to use rheo-fermentation properties to predict rheological properties of dough, thereby obtaining indirect information on both 3D printing properties and post-processing characteristics. The 3D printing behavior and baking quality of the dough were measured. A gluten content of 13% was found to be the most suitable for 3D printing and exhibited desirable performance during fermentation and baking. Pearson correlation analysis revealed a strong correlation between rheological properties and rheo-fermentation properties. Using partial least squares regression-based models, the coefficients of determination of the prediction for rheological parameters (G′, G″, η*) were 0.920, 0.854 and 0.863, respectively, with corresponding residual prediction deviation values of 3.063, 3.774, and 4.773. These findings suggest that 3D printing of bread dough products can be easily and successfully accomplished. [ABSTRACT FROM AUTHOR]