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To fully harvest the rich library of stellar elemental abundance dataavailable, we require reliable models that facilitate our interpretation ofthem. Galactic chemical evolution (GCE) models are one such set, and a key partof which are the selection of chemical yields from different nucleosyntheticenrichment channels, predominantly asymptotic giant branch (AGB) stars, Type Iasupernovae (SNe Ia), and core-collapse supernovae (CC-SNe). Here, we present ascoring system for yield tables based on their ability to reproduce proto-solarabundances within a simple parametrisation of the GCE modelling softwareChempy, which marginalises over galactic parameters describing simple stellarpopulations (SSPs) and interstellar medium physics. Two statistical scoringmethods are presented, based on Bayesian evidence and leave-one-outcross-validation and are applied to five CC-SN tables, (a) for all mutuallyavailable elements and (b) for a subset of the 9 most abundant elements. Wefind that the yields of Prantzos et al. (P18, including stellar rotation) andChieffi & Limongi (C04) best reproduce proto-solar abundances for the twocases, respectively. The inferred best-fit SSP parameters for (b) are$\alpha_\mathrm{IMF}=-2.45^{+0.15}_{-0.11}$ for the initial mass functionhigh-mass slope and $\mathrm{N}_\mathrm{Ia}=1.29^{+0.45}_{-0.31}\times10^{-3}$M$_\odot^{-1}$ for the SN Ia normalisation, which are broadly consistent acrosstested yield tables. Additionally, we demonstrate how Chempy can be used todramatically improve elemental abundance predictions of hydrodynamicalsimulations by plugging tailored best-fit SSP parameters into a Milky Wayanalogue from Gutcke & Springel. Our code, including a comprehensive tutorial,is freely available and can additionally provide SSP enrichment tables for anycombination of parameters and yield tables.

On the Optimal Choice of Nucleosynthetic Yields, IMF and Number of SNe Ia for Chemical Evolution Modelling