Climate-smart agricultural technologies offer transformative potential for achieving Sustainable Development Goals, especially in mitigating extreme weather impacts and enhancing food security. Despite this potential, adoption rates remain limited due to various factors, with perceived complexity playing a significant role. This study conducted a systematic review and meta-analysis to assess the influence of perceived innovation complexity on adopting climate-smart technologies. Using frameworks of the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology, we systematically reviewed 28 studies and conducted a meta-analysis of 15 studies across diverse geographic contexts. Our findings from the systematic review indicate inconsistent results on the impact of complexity on adoption due to the different items and scales used to measure the concepts of complexity across contexts, suggesting that there is a need for the development of a standardized scale to measure complexity. Results from the meta-analysis generated a summary effect size (r = 0.51, 95% CI = [0.05, 0.72], z = 6.78, p ≤ 0.0001), revealing a significant relationship between perceived complexity and adoption intent. The effect size of 0.51 indicates that higher complexity levels significantly decrease the likelihood of adoption intent for climate-smart technologies. Differences in CSA research trends across geographic regions highlight the need for tailored approaches to technology adoption that take into account the specific capabilities and constraints of each region. These findings provide valuable insights for policymakers, Extension professionals, and technology developers to design interventions to promote ease of use and enhance technology diffusion in sustainable farming practices and food security. These findings contribute to ongoing efforts to foster sustainable agricultural innovations, offering guidance to accelerate the global transition to more resilient farming systems.