Biological system modeling is an iterative process where uncertainties may arise, especially in the early stages. Static analysis tools are needed during each stage to help modelers detect unexpected behaviors early by automatically inferring properties about their models. However, the rule-based modeling language Kappa and its static analysis tool KaSa currently lack support for incomplete models. In this work, we extend Kappa to support incomplete models. In this setting, some rules are considered or not depending on the value of some Boolean parameters. We also generalize the current reachability analysis of the static analyzer KaSa to these parametric models, establishing relationships between properties and parameter values. Finally, we implement and evaluate our approach on example models.