MiCRO, a simple bilateral negotiation strategy that neither uses opponent modeling nor machine learning, and that requires no parameter tuning, demonstrated performance comparable to or better than many state-of-the-art methods. Its success raised concerns that existing benchmarking domains may be overly simplistic. This work addresses the open question of extending MiCRO to multilateral negotiations by proposing a new multilateral variant. We evaluate this variant against winners of ANAC 2015, 2017, and 2018, showing it outperforms these established agents. Additionally, an empirical game-theoretic analysis confirms that our multilateral MiCRO forms an empirical Nash equilibrium, highlighting its strategic robustness in complex multi-agent environments.