This paper reports development of a smartphone-based multispectral imaging system and its potential for diagnosis of various skin diseases quantitatively. To date, a variety of mobile devices have emerged as healthcare tools. In particular, when they are combined with advanced optical imaging techniques such as multispectral imaging techniques, it would be very beneficial for early diagnosis of malignant and non-malignant skin diseases and further quantitative monitoring of prognosis of the diseases after their treatment in ubiquitous environments. Recently, various mobile devices based on a smartphone gained much attention [1-3]. However, most of the devices were based on RGB color imaging as well as conventional image processing techniques and thus they have several limitations such as low spectral resolutions and less versatility when used to diagnose various skin diseases [4-6 22, 23]. To overcome these limitations, the development of a more advanced mobile skin diagnosis system with high quantitative capabilities must be achieved. Thus, we demonstrate development of a novel smartphone-based multispectral imaging system and its potentials of smartphone-based multispectral imaging and analysis for mobile diagnosis of various skin diseases. In this study, we underlie how to develop a smartphone-based multispectral imaging system. In particular, its unique calibration method, which is robust in mobile environments, is introduced. We also investigate its potentials for mobile diagnosis of various skin diseases including acne, seborrheic dermatitis, psoriasis, and etc. It was here found that the smartphone-based multispectral imaging and analysis using the system allowed us to quantitatively monitor acne regions during their treatments with benzoyl peroxide. The changes in the size and the severity of acne regions during the benzoyl peroxide treatments have been quantified using the system. Also, it was employed to discriminate between seborrheic dermatitis and psoriasis occurred on the scalp. The accuracy in discrimination between them at their early stage was found to be over 70%. Therefore, the results suggested that it has the potential as a mobile diagnosis tool for detection of both seborrheic dermatitis and psoriasis with high sensitivity and specificity at ubiquitous environments. Furthermore, we discuss its potential as a healthcare tool for recommendation of personalized cosmetics. Altogether, the smartphone-based multispectral imaging and analysis are highly useful for the early- and pre-detection of various skin diseases as well as quantitative/continuous monitoring of skin diseases with a low cost at home. Therefore, the results shown in this study demonstrate that it has great potential as a mobile-healthcare device to diagnose and manage skin lesions. It may furthermore be applicable to the detection of other malignant skin disease such as melanoma in ubiquitous environments.