Experimental modal analysis (EMA) is a technique that helps to identify the natural frequencies, modal damping, and mode shapes of a structure. The traditional approach to modal analysis involves using pointwise sensors like accelerometers, which only offer pointwise measurements. However, this method may not be sufficient for validating and updating Finite Element (FE) models using experimental data. On the other hand, numerical simulation of a structure’s dynamic behavior through FE Analysis (FEA) can provide full-field results, but the lack of points/DOFs creates a challenge for validating and updating the FE models. Digital Image Correlation (DIC) is a powerful and non-intrusive optical method that can provide full-field measurements of the mode shapes. DIC data can guide the FE model validation and update procedure, which enables a more accurate representation of the structure’s dynamic behavior. This enhanced predictive capability of the FE model allows for better decision-making regarding the structure’s performance and durability. This paper highlights the application of DIC in modal analysis and presents a comparison and data merging with traditional sensors to validate the obtained results. Additionally, the paper demonstrates the effectiveness of DIC in accurately characterizing the dynamic behavior of structures and improving the predictive capability of FE models through FE model validation and update.