Higher plant Rubisco activase (Rca) is a stromal ATPase responsible for reactivating Rubisco. It is a member of the AAA+ protein superfamily and is thought to assemble into closed-ring hexamers like other AAA+ proteins belonging to the classic clade. Progress towards modeling the interaction between Rca and Rubisco has been slow due to limited structural information on Rca. Previous efforts in the lab were directed towards solving the structure of spinach short-form Rca using X-ray crystallography, given that it had notably high thermostability in the presence of ATP-γS, an ATP analog. However, due to disorder within the crystal lattice, an atomic resolution structure could not be obtained, prompting us to move to negative stain electron microscopy (EM), with our long-term goal being the use of cryo-electron microscopy (cryo-EM) for atomic resolution structure determination. Thus far, we have screened different Rca constructs in the presence of ATP-γS, both the full-length β-isoform and truncations containing only the AAA+ domain. Images collected on preparations of the full-length protein were amorphous, whereas images of the AAA+ domain showed well-defined ring-like assemblies under some conditions. Procedural adjustments, such as the use of previously frozen protein samples, rapid dilution, and minimizing thawing time were shown to improve complex assembly. The presence of Mn2+ was also found to improve hexamer formation over Mg2+. Calculated class averages of the AAA+ Rca construct in the presence of ATP-γS indicated a lack of homogeneity in the assemblies, showing both symmetric and asymmetric hexameric rings. To improve structural homogeneity, we tested buffer conditions containing either ADP alone or different ratios of ATP-γS to ADP, though results did not show a significant improvement in homogeneity. Multiple AAA+ domain preparations were evaluated. Because uniform protein assembly is a major requirement for structure solution by cryo-EM, more work needs to be done on screening biochemical conditions to optimize homogeneity.