The stability analysis of neutral type neural networks (NNs) with dynamic delay structures presents a significant challenge due to the inherent complexity of such systems. In this paper, we propose a novel perspective for analysing the stability of neutral type NNs with dynamic delay structures. Our approach leverages recent advancements in delay-dependent stability analysis techniques and integrates them with innovative methodologies for handling dynamic delay structures. Specifically, we introduce a novel Lyapunov-Krasovskii functional incorporating delay partitioning strategies tailored to dynamic delay structures. The derived stability criteria offer a comprehensive framework for assessing the stability of neutral type NNs under various dynamic delay scenarios. Numerical simulations demonstrate the effectiveness and superiority of the proposed approach over existing methods, highlighting its potential for practical applications in complex neural network systems.