One of the limitations is data quality, the predictive models rely entirely on large and accurate datasets to make realistic predictions. So if the data is inaccurate, biased or incomplete then the model will be flawed.
The next is overfitting which happens when a model is trained on a particular dataset and becomes too complicated makes it difficult to generalise new data. Because of this it can make inaccurate predictions and poor performance.
Next is changing conditions, predictive analytics models are made to predict future outcomes based on previous data. However, the future is very uncertain and because of this the conditions can change quickly so it can be very difficult to predict accurately.
And lastly ethical concerns can make it difficult to predict analysis because of ethical concerns such as bias or privacy. Predictive models can have an already existing bias and discrimination. Also predictive analytics can have privacy concerns due to if personal data is used without consent or is shared with another third party.
https://www.devopsschool.com/blog/what-are-the-limitations-of-predictive-analytics/
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