There is a consensus that motor recovery post-stroke primarily depends on the degree of the initial connectivity of the ipsilesional corticospinal tract (CST). Indeed, if the residual CST connectivity is sufficient to convey motor commands, the neuromotor system continues to dominantly use the CST, and motor function recovers up to 80%. In contrast, if the residual CST connectivity is insufficient, hand/arm dexterity barely recovers, even as the phases of stroke progress. Instead, functional upregulation of the reticulospinal tract (RST) often occurs. In this study, we construct a computational model that reproduces the dependence of post-stroke motor recovery on initial CST connectivity. The model emulates biologically plausible evolutions of primary motor descending tracts, based on activity-dependent or use-dependent plasticity and the preferential use of more strongly connected neural circuits. The model replicates several segments of the empirical evidence presented by Fugl-Meyer subscores, which presumably change differently depending on the degree of initial CST connectivity post-stroke, providing several insights into the interactive dynamics of primary descending motor tracts. We discuss findings from the proposed model along with the well-known proportional recovery rule. This modeling study is expected to benefit the design of therapies for post-stroke recovery.