An innovative extension that includes Pythagorean fuzzy sets (PFSs), Intuitionistic fuzzy sets (IFSs), and ordinary fuzzy sets (FS) is Fermatean fuzzy sets (FFSs). Fuzzy similarity measures are essential in many areas, including multi-criteria decision-making (MCDM), pattern recognition (PR), and classification. These measurements are important, especially in MCDM, where deciding on criteria weights is important in a fuzzy framework. Therefore, the goal of this work is to develop a new similarity measures for FFSs, which is a reliable means of assessing object resemblances. This study introduces a new distance measure designed to evaluate differences between FFSs. Additionally, by utilizing our creative abilities, a dynamic and effective MCDM approach to the orthopair fuzzy TODIM algorithm has been devised.