Procedures that include flexibility cause fluctuation and other individual differences in experimenter behavior. This study aims to quantify such fluctuation and individual differences in procedures by modelling human behavior. In water measurement, for example, considerable longitudinal data must be compiled, especially monitoring the progress in water height. By analyzing the principal component, the “planning” and “adjustment” components are obtained. The human behavior model was then created to link principal component score to experimenter characteristics. In this model it was assumed that the principal component score was decided by procedural elements such as water velocity, and by contextual elements such as experimenter trial number, final results of previous experiments, and accumulated minutes. Model coefficients are calculated as parameters of each experimenter by fitting the model. Parameter sign revealed that experimenters tend to respond to water velocity change by “adjustment”, and “planning” is used as repeated time increase and failures in previous time. Prediction values were in good agreement with actual values, proving that mathematical modelling of human behavior has the potential for effectively predicting individual behavior.