We consider the asymptotic normalcy of families of random variables X which count the number of occupied sites in some large set. If inlineImage" height="24" width="128" alt="View the MathML source" title="View the MathML source" src="/sd/grey_pxl.gif" data-inlimgeid="1-s2.0-S0097316516000224-si1.gif">iner hidden"> is the generating function associated to the random sets (i.e., there are pjiner hidden"> choices of random sets with j occupied sites), we will consider the probability measures Prob(X=m)=pmzm/P(z)iner hidden">, for z real positive. We give sufficient criteria, involving the location of the zeros of P(z)iner hidden">, for these families to satisfy a central limit theorem (CLT) and even a local CLT (LCLT); the theorems hold in the sense of estimates valid for large N (we assume that Var(X)iner hidden"> is large when N is). For example, if all the zeros lie in the closed left half plane then X is asymptotically normal, and when the zeros satisfy some additional conditions then X satisfies an LCLT. We apply these results to cases in which X counts the number of edges in the (random) set of “occupied” edges in a graph, with constraints on the number of occupied edges attached to a given vertex. Our results also apply to systems of interacting particles, with X counting the number of particles in a box Λ whose size |Λ|iner hidden"> approaches infinity; P(z)iner hidden"> is then the grand canonical partition function and its zeros are the Lee–Yang zeros.