  The associated production of a $b\bar{b}$ pair with a Higgs boson could
provide an important probe to both the size and the phase of the bottom-quark
Yukawa coupling, $y_b$. However, the signal is shrouded by several background
processes including the irreducible $Zh, Z\to b\bar{b}$ background. We show
that the analysis of kinematic shapes provides us with a concrete prescription
for separating the $y_b$-sensitive production modes from both the irreducible
and the QCD-QED backgrounds using the $b\bar{b}\gamma\gamma$ final state. We
draw a page from game theory and use Shapley values to make Boosted Decision
Trees interpretable in terms of kinematic measurables and provide physics
insights into the variances in the kinematic shapes of the different channels
that help us complete this feat. Adding interpretability to the machine
learning algorithm opens up the black-box and allows us to cherry-pick only
those kinematic variables that matter most in the analysis. We resurrect the
hope of constraining the size and, possibly, the phase of $y_b$ using kinematic
shape studies of $b\bar{b}h$ production with the full HL-LHC data and at
FCC-hh.
