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When would you choose logistic regression over gradient boosting?

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When interpretability or calibrated, stable probabilities matter, when data is small, when features are already well engineered and roughly linear in effect, or when the model must be simple to deploy and audit. Otherwise boosting usually wins on accuracy for tabular data.

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