We analyze results generated by large-scale molecular-dynamics simulations of self-interstitial clusters in crystalline silicon using a recently developed computational method for probing the thermodynamics of defects in solids. In this approach, the potential-energy landscape is sampled with lengthy molecular-dynamics simulations and repeated energy minimizations in order to build distribution functions that quantitatively describe the formation thermodynamics of a particular defect cluster. Using this method, a comprehensive picture for interstitial aggregation is proposed. In particular, we find that both vibrational and configuration entropic factors play important roles in determining self-interstitial cluster morphology. In addition to the expected role of temperature, we also find that applied (hydrostatic) pressure and the commensurate lattice strain greatly influence the resulting aggregation pathways. Interestingly, the effect of pressure appears to manifest not by altering the thermodynamics of individual defect configurations but rather by changing the overall energy landscape associated with the defect. These effects appear to be general and are predicted using multiple, well-tested, empirical interatomic potentials for silicon. Our results suggest that internal stress environments within a silicon wafer (e.g., created by ion implantation) could have profound effects on the observed selfinterstitial cluster morphology.