We show how the renormalization group approach can be used to prove quantitative central limit theorems (CLTs) in the setting of free, Boolean, bi-free and bi-Boolean independence under finite third moment assumptions. The proofs rely on the construction of a contraction on a subspace of probability measures over $\mathbb{R}$ (or $\mathbb{R}^2$) equipped with a suitable metric, which has the appropriate analogue of a Gaussian distribution as a fixed point (for instance, the semi-circle law in the case of free independence). In all cases, this yields a convergence rate of $1/\sqrt{n}$, and we show that this can be improved to $1/n$ in some instances under stronger assumptions.