Pressure drop is a key factor that indicates flooding phenomenon in packed columns. However, it is difficult to apply statistical process control (SPC) to this variable for flooding prognosis. This is because, even if the system is operated below the flooding point, both the mean and variance of pressure drop may continue to change, because of fluctuations in either the gas or the liquid flow rate. As such, it is incorrect to represent the measured values of pressure drop with a certain distribution. Fortunately, it has been observed that the inherent distinction before and after the occurrence of flooding is the shift in the degree of steadiness (DOS) of the pressure drop trajectory. This is the motivation for the research presented in this paper. First, an assessment approach is introduced to quantify the concerned DOS of the pressure drop trajectory in each time window. Thereafter, instead of the original process variable, the DOS is monitored for flooding prognosis. Because of the lack of knowledge on the exact distribution of DOS, a nonparametric charting technique is adopted, which can be implemented in a simple and efficient manner. The feasibility of the proposed method is then illustrated using the experimental results on flooding prognosis in a packed column.