Bubble-induced turbulence (BIT) is a two-phase flow phenomenon characterized by complex interfacial interactions that fundamentally alter the resulting liquid turbulent kinetic energy distribution, budgets, and scales. Incorporating this complexity into a BIT model remains a formidable challenge, as existing two-equation BIT closures struggle with accurately predicting the turbulent kinetic energy and mean flow profiles. The present work assembles a BIT model that incorporates additional physical understanding into its formulation by leveraging insights garnered from experiments, DNS, and previous assessment. The model comprises new turbulent viscosity and time-scale formulations, in addition to optimized values for the modulation parameter, dissipation coefficient, and newly proposed turbulent viscosity multiplier. Improved model performance is demonstrated through simulation of air/water experimental cases and direct comparison with existing closures, which includes qualitative inspection of individual sets as well as quantitative assessment of the turbulent kinetic energy error distribution. Future work delving into momentum closure development, new experimental campaigns, and DNS parametric studies is motivated and linked to BIT model improvements. Published by Elsevier Ltd.