  We infer the progenitor mass distribution for 22 historic core-collapse
supernovae (CCSNe) using a Bayesian hierarchical model from D\'iaz-Rodr\'guez
et al. (2018). For this inference, we use the local star formation histories to
estimate the age for each supernova (SN) as inferred in Williams et al. (2018).
These star formation histories often show multiple bursts of star formation;
our model assumes that one burst is associated with the SN progenitor and the
others are random bursts of star formation. The primary inference is the
progenitor age distribution. Due to the limited number of historic SNe and
highly uncertain star formation at young ages, we restrict our inference to the
slope of the age distribution and the maximum age for CCSNe. Using single-star
evolutionary models, we transform the progenitor age distribution into a
progenitor mass distribution. Under these assumptions, the minimum mass for
CCSNe is ${M_\textrm{min}}~=~8.60^{+0.37}_{-0.41} \ M_\odot$ and the slope of
the progenitor mass distribution is $\alpha = -2.61^{+1.05}_{-1.18}$. The
power-law slope for the progenitor mass distribution is consistent with the
standard Salpeter initial mass function ($\alpha = -2.35$). These values are
consistent with previous estimates using precursor imaging and the age-dating
technique, further confirming that using stellar populations around SN and
supernova remnants is a reliable way to infer the progenitor masses.
