Fouling is the formation of a layer of deposits on heat transfer surfaces of undesirable materials or compounds. It is influenced by fluid property that is the presence of flow rate and fluid temperature. Fouling on heat exchanger is a very complex phenomenon in such a way that difficult to analyze analytically. So it takes a mathematical fouling model to predict fouling rate in order to increase the efficiency of the heat exchanger caused by the existence of fouling. The model was developed based on the first principal model with the advantage that the model has more detailed potential phenomena regarding the occurance of fouling, nonetheless the data that this research used is difficult to find. As broadly known, the advantages of an empirical model was able to get fouling rate with ease and it agree with the form of fouling that occurs in the plant, but it could not describe the phenomenon that occurs. Therefore it takes a developed fouling model by combining the first principal models and empirical equations to become a semi-empirical model on heat excanger which could describe the phenomenon and also follow the pattern to accommodate the linear, exponential and sigmoid characteristics. The Boltzmann-sigmoidal function captures the fouling initiation period which is the major advantage of this model over the other type of models used by previous researchers. This paper presents the development of empirical models for an industrial HEN (Heat Exchanger Network) using the plant operating data. The fouling models are developed and shown to describe the fouling resistance over time in a crude preheat train with reasonable accuracy.