  We propose a novel dynamical model for blood alcohol concentration that
incorporates $\psi$-Caputo fractional derivatives. Using the generalized
Laplace transform technique, we successfully derive an analytic solution for
both the alcohol concentration in the stomach and the alcohol concentration in
the blood of an individual. These analytical formulas provide us a
straightforward numerical scheme, which demonstrates the efficacy of the
$\psi$-Caputo derivative operator in achieving a better fit to real
experimental data on blood alcohol levels available in the literature. In
comparison to existing classical and fractional models found in the literature,
our model outperforms them significantly. Indeed, by employing a simple yet
non-standard kernel function $\psi(t)$, we are able to reduce the error by more
than half, resulting in an impressive gain improvement of 59 percent.
