Maji et al. pioneered a basic inquiry into the field of uncertainty handling by initiating a study involving fuzzy sets and soft sets. In 2016, Acikgoz and Nikal Tas [2] laid the framework for later advances by defining the fundamental structures of binary soft sets across two initial universal sets, U1 and U2. In 2020, J. Subhashini and P. Gino Metilda [5] investigated the fundamental structure of fuzzy binary soft sets, gaining valuable insights into the merging of fuzzy and soft set theories. Building on these advances, we introduced an extension namely, Intuitionistic Fuzzy Binary Soft Sets (IFBSS), over two initial universal sets, U1 and U2. We define the distance between Intuitionistic Fuzzy Binary Soft Sets using two term approach (involves both the membership and non-membership function). We present four fundamental distance metrics: Hamming distance, normalized Hamming distance, Euclidean distance, and normalized Euclidean distance.