A power generating system in a steam power plant is a complex one. This system involves a large number of variables containing information concerning the operation conditions. It can also be seen as an important asset in both power generation and energy portfolios. At the Asam-asam power plant of South Kalimantan, the complexity of the system has led to difficulties in explaining the apparently steady decrease in the output power. The amount of data collected is simply too big and the dimension too high for analysis purposes based on conventional thermodynamics. This study was performed to tackle the problem using statistical modelling. This approach can accommodate empirical behaviors of the variables and the probabilistic nature of the system. Information obtained from this modelling can be valuable for various purposes. The method consists of literature review, model development, data collection and analysis, and model fitting. Generalized additive models were chosen. Data were available from the company as observed from more than 140 variables. The resulting model identifies variables significantly related to the output power and locate subsystems whose fluctuating behaviors are usually ignored in a conventional thermodynamic analysis. A direction for future research is recommended.