Software predictors are not crystal balls, but they are essential decision support systems . Their value depends entirely on organizational learning – collect actual effort data, recalibrate models every quarter, and always present estimates as probabilistic ranges, not fixed numbers. In Agile contexts, velocity and burn-up charts are often more practical predictors than legacy COCOMO-style models. “It is better to be roughly right than precisely wrong.” — John Maynard Keynes (often quoted in software estimation literature)
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