Log normal is something like Y = X1 * X2 * X3 * .. * XN, where Xi are iid positive random variables?

Through central limit theorem one could argue Y ~ exp(N * normal) for large N.

Strictly speaking, 1/N log Y converges to a normal rv in distribution.