There are a number of instances where models are a little less than adequate to explain the things they represent. A computer program used to model the behavior of wildfires, for instance, did not even come close to predicting events in the recent Florida wildfires. When variables as minute as a chance puff of wind or a few dead trees could alter the path of the fire on a much larger scale, researchers couldn't make accurate predictions based on a simple model. Often, the quest to make the complex simple eliminates important parts of a model system. From this point of extreme reduction, there's nowhere to go but up.
Science tends too much toward reductionism.
That's why science and society are having trouble. It depends on the situation. There's a fine line to walk when trying to crystallize myriad and abstract ideas into patterns that can be understood. Like art, too much detail obscures the concept altogether, while too little leaves the model insufficient to explain an idea. Models aren't only used to explain situations to the public, however.