Due to stringent environmental regulations, wastewater treatment plants are always challenged to meet new constraints in terms of water pollution prevention. In such an effort, the number of sensors and data available in the plants have increased considerably during the last decades. However, the quality of the collected data and the sensor reliability are often poor mainly due to the hostile environment in which the measurement equipment has to function. In this work, we present the design of an array of soft-sensors to estimate the nitrate concentration in the post-denitrification filter unit of the Viikinmaki wastewater treatment plant in Helsinki (Finland). The developed sensors aim at supporting the existing hardware analyzers by providing a reliable back-up system in case of malfunction. The main stages of the soft-sensors' design are discussed and the development illustrated in detail, starting from the preliminary preprocessing of the available process measurements where sample and variable selection has been performed, toward the calibration of the regression models and discussion on the performance results. The estimation accuracy together with the light computational cost of the developed soft-sensors demonstrate their potential for an on-line implementation in the plant's control system. (C) 2012 Elsevier Ltd. All rights reserved.