Waste management is currently a very actual area which is subjected to many changes and ongoing development. The aim is to maximize the use of waste as secondary material. Especially, processing facilities must respond to new rules in time because the construction of a new facility or modification of existing one usually takes several years. The efficient waste management planning requires both quantitative and qualitative estimates of future waste production reflecting analyzed timeframe. The forecasting of waste production is the challenging task due to the various barriers in terms of short time series, faulty reporting data or production sudden shift caused by multiple factors such as legislation, technology or system changes. These external influences can reverse the waste production substantially and then the historical data loses its explanatory value due to trend change and waste production in the new direction. However, the trend in historical data can be successfully modeled by S-curve function. The proposed method analyses the waste production historical data by combining credibility theory (usually used in the insurance industry) and the evaluation of trends in the time series. The so-called credibility approach uses the principles based on the combination of the collective and individual information to improve estimation accuracy. In this way, the classic S-curve trend model is corrected by overall information and utilizes the already known development of separation in other areas. The presented procedure determines the credibility of the individual data according to fulfilling separation potential. The testing dataset comes from the bio-waste production in the Czech Republic on the micro-regional level. In addition, the difference between rural and urban area is taken into account. The new methodology is generally applicable when the waste production was influenced in history and thereby the trend was changed.