Heart failure is a clinical condition in which the heart’s pump capacity is insufficient to meet the metabolic demands of the body. Fluid build-up in the lungs (i.e. congestion) is one of the major problems for these patients. Early identification of congestion could result in faster treatment strategies and therefore could prevent expensive hospitalizations. However, currently there is no gold standard method to accurately detect fluid build-up in real-time in daily life. The goal of the current study is to optimize the electrode positioning for the development of a wearable bioimpedance sensor to monitor pulmonary fluid build-up for congestive heart failure patients. Hereto, a finite element modelling approach was used. Using modelling, four different electrode configurations (1. Electrodes left side to right side of the thorax, 2. Electrodes vertically aligned on the left side of the thorax, 3. Electrodes in a rectangle on the left side of the thorax and 4. Electrodes horizontally on the left side of the thorax) were tested for sensitivity and selectivity to the lung area and for the ability to detect fluid accumulation in the lungs. In addition, the effect of body composition on the measurements was tested. All four electrode configurations showed medium to high sensitivity, selectivity and ability to detect lung water. In addition, all configurations were sensitive to changes in adipose or muscle content. Configuration 1 (left side to right side) was able to capture information from both lungs as a result of its placement. The other configurations were sensitive to fluid changes in the left lung. The results indicate that modelling can be used to optimize the electrode configuration for bioimpedance measurements and can help in getting more insight into the contributions of the different tissues to the measured signal.