To achieve a good ecological status for all water bodies in time, the Water Framework Directive raises serious problems for political decision-makers and water managers who adress many questions for aquatic scientists. During the last ten years, most of the research works carried out within the scope of the WFD was dedicated to development of bioassessment tools based on different biological quality elements (algae, benthic fauna and fish), using data from national monitoring networks. However, not all water bodies are surveyed across France, due to both technical limitations and economic reasons. Within this context, it is therefore very important to strengthen the direct monitoring of water bodies to develop efficient methods for the classification of non-monitored water bodies based on robust and homogeneous predictive models based on causal relationship between biological quality elements (and consequently ecological status) and multiple impairments and stressors at catchment and local scales. We developed a model for the classification of non-monitored water bodies. This model is based on land cover, water quality and hydromorphological pressures and allow to make a spatial extrapolation of ecological status at the scale of water bodies. It is developed using classification and regression tree method and have a very good predictive efficiency. We complete this extrapolation model with other models (using partial least square regression methods) aiming to make the diagnostic of pressures responsible for bad status of water bodies. These models explain benthic invertebrates, diatoms and fish index using land cover, water quality and hydromorphological pressures and allow to assess the relative impact of each type of pressure and the response of each biological quality element. The development of such a pressures/impact models is a very promising alternative to compensate the availability of local monitoring data. Even if these models are of course not able to solve all water manager's problems, they may help them to optimize monitoring programs and to assign an ecological status to those water bodies which are not surveyed, based on the pressures acting at a local and/or regional scales and the statistical relationships established for surveyed sites located in the same pressures context.