We propose a robust non-contact method to accurately estimate peripheral oxygen saturation (SpO) using a smartphone-based imaging photoplethysmography. The method utilizes the built-in color camera as a remote sensor and the built-in flashlight as illumination to estimate the SpO. Following the ratio of ratios between green and red channels, we introduce a multiple linear regression algorithm to improve the SpO estimation. The algorithm considers the ratio of ratios and the reflectance images recorded at the RGB channels during a calibration process to obtain a set of weighting coefficients to weigh each contributor to the final determination of SpO. We demonstrate the proposed smartphone-based method of estimating the SpO on five healthy volunteers whose arms are conditioned by a manual pressure cuff to manipulate the SpO between 90∼100% as detected simultaneously by a medical-grade pulse oximeter. Experimental results indicate that the overall estimated error between the smartphone and the reference pulse oximeter is 0.029 ± 1.141%, leading to a 43% improvement over the conventional ratio of ratios method (0.008 ± 2.008%). In addition, the data sampling time in the current method is 2 seconds, similar to the sampling cycle used in the commercial medical-grade pulse oximeters.