PurposeMobile phones are radically transforming micro-finance in Sub-Saharan Africa, and Kenya, in particular. The introduction of the micro-financial transaction mobile phone application, “MPesa,” created a means to facilitate micro-transactions without the need for an intermediary, such as a banking system. The purpose of this paper is to posit an econophysics model to predict the value of Mpesa for Kenyan and South African consumers. The econophysics framework posits several fitness matrices and a distance measure that can account for the concepts of mass, distance, momentum, velocity, action, and force. The authors begin with a table of the match between the physics concepts and the economic concepts followed by the vector model that utilizes these concepts for the MPesa application case. In this paper, the authors will argue that MPesa succeeded in Sub-Saharan African countries, such as Kenya, because the fit between what this group of customers needed and the solutions Safaricom’s MPesa offered was a better fit with a smaller distance to adoption than in the South African case.Design/methodology/approachThe research develops an econophysics approach to the assessment of micro-finance development in Sub-Saharan countries.FindingsThe research shows clearly the reasons of the success of MPesa in Kenya in comparison of its relative failure in South Africa: the distance between customers’ expectations and the system supply.Research limitations/implicationsThe research is limited to two case studies and needs to be extended to other contexts, in order to demonstrate its robustness, especially with regard to the intangible dimension, e.g., the distance between a system potential and what it really offers.Practical implicationsThe research shows the importance of system’s characteristics in its success.Social implicationsThe social implications are very high, especially in this case, where micro-finance is a high stake for developing societies.Originality/valueThis is one of the first works to develop an econophysics approach for the evaluation of the key characteristics of a system.