This study introduces a novel bacterial-based molecular communication (BBMC) model for nanoscale information exchange, harnessing the chemotactic behavior of Escherichia coli (E. coli). A comprehensive 3D simulation framework is developed to analyze the impact of key parameters diffusion coefficient (D), chemoattractant release rate (Q), receiver (RX) speed (u), and initial transmitter-receiver distance (d) on communication performance. Results indicate that lower D values enhance the formation of chemoattractant gradients, leading to improved signal clarity and efficiency. Conversely, higher RX speeds distort these gradients, increasing signal reach time and reducing success rates. Elevated Q values significantly broaden the sensing range and improve reliability, particularly over larger distances, though their effect is diminished at high RX speeds. Notably, success rates drop sharply as d approaches the theoretical sensing threshold, underscoring the critical need for parameter tuning. Experimental results validate these findings and reveal a threshold beyond which bacterial movement becomes random, limiting effective signal transmission. These insights contribute to optimizing BBMC systems for greater efficiency and reliability. Applications include targeted drug delivery, environmental biosensing, and synthetic biology, where precise bacterial signaling is essential. The study also demonstrates simulation as a scalable, cost-efficient alternative to experimental methods, addressing complexity and feasibility in real-world scenarios.