We review recent work on the application of fluctuation analyses of time series for pattern classification in nondestructive materials inspection. These analyses are based on the evaluation of time-series fluctuations across time intervals of increasing size, and were originally introduced in the study of fractals. A number of examples indicate that this approach yields relevant features allowing the successful classification of patterns such as (i) microstructure signatures in cast irons, as probed by backscattered ultrasonic signals; (ii) welding defects in metals, as probed by TOFD ultrasonic signals; (iii) gear faults, based on vibration signals; (iv) weld-transfer modes, as probed by voltage and current time series; (v) microstructural composition in stainless steel, as probed by magnetic Barkhausen noise and magnetic flux signals.