<p>The goal of this work was to characterize the physical, chemical, and mechanical property anisotropy and self-healing ability of shape memory polymer blends for use in the additive manufacturing platform of fused filament fabrication. The overall premise of this work is implementing materials that can be healed upon damage to lower the amount of polymer waste in the environment. In this work, we melt compounded binary and ternary blends of various linear polyesters: (1) a binary blend composed of polycaprolactone (PCL) and thermoplastic urethane (TPU) and (2) a ternary blend composed of PCL, TPU, and polylactic acid (PLA) where, in both cases, the constituents were combined in equal parts by weight. The effect of raster direction on the mechanical and shape memory properties was assessed by fabricating tensile test specimens with different print raster patterns. The materials were characterized using different techniques such as Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) to evaluate fracture surfaces of spent tensile, optical microscopy (OM) to characterize print defects and polymer microstructure, as well as a cut test to assess the ability of these materials to self-heal. It was found that the relationship between thermomechanical processing and mechanical properties is dependent on print raster pattern. Both blends exhibited a high level of mechanical property anisotropy, consistent with other polyesters used in additive manufacturing. It was also found that unoptimized print parameters for the ternary blend led to the failure mechanism of delamination. Finally, the ternary blend exhibited a lower percent reduction in strength after subjecting the specimens to a thermal recovery cycle after a cut test.</p>