Predictive models are limited by the quality and completeness of the input data. Inaccurate data can lead to flawed predictions. Additionally, models often rely on assumptions that may not hold true in all scenarios. For example, the assumption of homogeneous mixing in a population doesn't account for variations in social behavior. Moreover, unforeseen factors like mutations in a virus can disrupt predictions.
