Pattern matching in DNA sequences is a crucial task in bioinformatics, with applications ranging from identifying regulatory elements to detecting genetic mutations. In this study, we propose a novel approach using Bidirectional Long ShortTerm Memory (Bi-LSTM) networks to perform pattern matching in DNA sequences. By leveraging the sequential nature of DNA sequences and the ability of Bi-LSTM networks to capture long-range dependencies, we achieve accurate and efficient pattern matching. Through extensive experiments on real-world DNA datasets, we demonstrate the effectiveness of our approach in identifying complex patterns in DNA sequences with high accuracy.