Currently, research on the scale effect mainly concentrates on revealing and describing the phenomenon; little work has been done to model the scaling of analysis indicators along with the scale change of the data. Such models can help explain and estimate the scale effect and are thus of great interest. As patch morphology significantly influences patch evolution over data scale transformation, this study proposes a model that applies patch morphology metrics to explain and estimate the change in the patch and category area ratio in the upscaling of raster categorical data. In the experimental evaluation, area scaling of GlobeLand30 data under majority aggregation is studied intensively. Two metrics—the ratio of the patch area after aggregation to its original area and the ratio of the category area after aggregation to its original area—are used in this evaluation. The experimental results indicate that this model can adequately describe the pattern of the patch area change and precisely estimate the category area change arising from the resolution change. It is also demonstrated that the spatial distribution of patches has much less influence on the change in the category areas compared with the patch morphology. Additionally, the modeling approach in this study may also be adopted to investigate the scaling of other landscape metrics.