In this paper, we propose a modified RLS algorithm with Adaptive Forgetting Factor using a low-complexity forgetting factor update equation. The conventional AFF-RLS method has a high-complexity update equation to update forgetting factor. In order to reduce complexity, an approximated version of the AFF-RLS method had been derived by Song. But this modified AFF-RLS method shows degraded performance because it suffers from `gradient error amplification' problem. In order to obtain the same performance as AFF-RLS with relatively low computational cost, we noted that AFF-RLS had been derived by `method of steepest descent', and we use normalization technique which is used in NLMS. The Experiment result shows that the proposed method has almost same performance as the conventional AFF-RLS method with relatively low-complexity.