We assess the suitability of different charge models and computational strategies, such as analyzing the meta/para carbon atoms, the attached meta/para hydrogen atoms, and additional ring substituents in deriving computed parameters that are correlated with Hammett parameters. In doing so, we demonstrate a wide range of performance across the different computational protocols and observe stark and surprising differences in the ability of computational parameters to capture para vs. meta-electronic effects. Additionally, we apply these methods to parametrize multiply-substituted aromatics, compare against experimental rate data, and develop suggested best practices for "bottom-up" computational models of inductive and resonance effects as encapsulated by Hammett parameters. We propose linear regression formulae to derive Hammett parameters for substituents without experimental data, and for multiply substituted aromatic rings from computed descriptors.