  In this paper we consider the product of two independent random matrices
$\mathbb X^{(1)}$ and $\mathbb X^{(2)}$. Assume that $X_{jk}^{(q)}, 1 \le j,k
\le n, q = 1, 2,$ are i.i.d. random variables with $\mathbb E X_{jk}^{(q)} = 0,
\mathbb E (X_{jk}^{(q)})^2 = 1$. Denote by $s_1, ..., s_n$ the singular values
of $\mathbb W: = \frac{1}{n} \mathbb X^{(1)} \mathbb X^{(2)}$. We prove the
central limit theorem for linear statistics of the squared singular values
$s_1^2, ..., s_n^2$ showing that the limiting variance depends on $\kappa_4: =
\mathbb E (X_{11}^{1})^4 - 3$.
