<p>In this study, we investigate the global Mittag–Leffler synchronization of fractional-order complex-valued bidirectional associative memory (BAM) neural networks by employing linear feedback controllers. Unlike many existing approaches that decompose complex-valued systems into separate real and imaginary parts, our method directly handles complex-valued fractional-order dynamics, preserving the inherent structure and reducing complexity. We develop new sufficient conditions for synchronization by constructing a Lyapunov function and applying the generalized Gronwall-like inequality, leading to less restrictive criteria compared to conventional methods. Two linear feedback control strategies—single-state and whole-state controllers—are designed to enhance flexibility and robustness under time delays and uncertainties. Numerical simulations are presented to validate the theoretical results and demonstrate the effectiveness of the proposed approach.</p>