The accelerometers embedded within smartphones may be a promising tool to capture gait patterns outside the laboratory and for extended periods of time. The current study evaluated the agreement and reliability of gait measures derived from a smartphone accelerometer system, compared to reference motion capture and footswitch systems during treadmill walking. Seventeen healthy young adults visited the laboratory on three separate days and completed three 8-minute treadmill walking trials, during each visit, at their preferred walking speed. The inter-stride interval series was calculated as the time difference between consecutive right heel contacts, located within the signals of the smartphone accelerometer, motion capture, and footswitch systems. The inter-stride interval series was used to estimate common linear gait measures and nonlinear measures, including fractal scaling index, approximate entropy, and sample entropy. Bland Altman plots with 95% limits of agreement and intraclass correlation coefficients assessed agreement and reliability, respectively. The smartphone system was found to be within the acceptable limits of agreement when compared to either reference system. The intraclass correlation coefficients values revealed moderate-to-excellent reliability for the smartphone system, with greater reliability found for linear compared to nonlinear measures and were similar to both reference systems, except for the fractal scaling index. These findings suggest the smartphone accelerometer system is a valid and reliable method for estimating linear and nonlinear gait measures during treadmill walking.