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I have good model fitness and path results. However, the predictive relevance is very poor. How can i improve this condition? I mean how can i get good predictive relevance? Your valuable answer will support me a lot.

There is unfortunately no easy answer to this question.
We know from the literature that models that fit well, do not necessarily need to predict well. In fact, models that fit well can often predict more poorly than models that do not fit so well. This is the problem of overfitting, where the model is fitting to well to the sample it was estimated on, but does not generalize to other datasets.
Often, less complex models predict better, while more complex models fit better.

At the end, you may have to rethink your model or acknowledge this shortcoming for future research.