Consumer, business and governmental entities increasingly rely on spatial decision support systems (SDSS) for decision-making involving geospatial data. Understanding user- and task-characteristics that impact decision performance will allow developers of such systems to maximize geospatial decision-making performance. Furthermore, scholars will benefit from a more comprehensive understanding of what specific characteristics influence decision-making as such knowledge can guide future research in the decision sciences domain. This paper provides a synthesis of geospatial reasoning ability, task-complexity, geovisualization and decision-performance research. A two-factor experiment designed to measure the impact of geospatial reasoning ability on decision-performance is performed. Two treatments, problem-complexity and map-complexity, are investigated for their moderating role on decision-performance. A partial least squares analysis is performed to assess the experiment results. Cognitive Fit Theory is used as the theoretical framework of this study and is extended, along with research in decision-performance and geospatial reasoning ability