The simultaneous quantification of multiple proteins is crucial for accurate medical diagnostics. A promising technology, the multiplex colorimetric immunoassay using encoded hydrogel microparticles, has garnered attention, due to its simplicity and multiplex capabilities. However, it encounters challenges related to its dynamic range, as it relies solely on the colorimetric signal analysis of encoded hydrogel microparticles at the specific time point (i.e., end-point analysis). This necessitates the precise determination of the optimal time point for the termination of the colorimetric reaction. In this study, we introduce real-time signal analysis to quantify proteins by observing the continuous colorimetric signal change within the encoded hydrogel microparticles. Real-time signal analysis measures the "slope", the rate of the colorimetric signal generation, by focusing on the kinetics of the accumulation of colorimetric products instead of the colorimetric signal that appears at the end point. By developing a deep learning-based automatic analysis program that automatically reads the code of the graphically encoded hydrogel microparticles and obtains the slope by continuously tracking the colorimetric signal, we achieved high accuracy and high throughput analysis. This technology has secured a dynamic range more than twice as wide as that of the conventional end-point signal analysis, simultaneously achieving a sensitivity that is 4−10 times higher. Finally, as a demonstration of application, we performed multiplex colorimetric immunoassays using real-time signal analysis covering a wide concentration range of protein targets associated with pre-eclampsia.