Despite many efforts by governments, international and local non-governmental organizations, and bilateral and multilateral donors, poverty and malnutrition remain prevalent concerns. The need to overcome the dynamic and stochastic nature of poverty and malnutrition to achieve long-term development goals has brought attention to the role that shocks and stressors play in determining well-being outcomes. Resilience, the capacity over time of avoiding poverty, however defined, in the face of multiple shocks and stressors, picks up this concern. The concept has increased in popularity in development circles during the last decade, but, to date, no consensus has been reached on how to measure it empirically. This paper carries out a comparative analysis of three of the most currently popular resilience measurement methods, with the ultimate goal of determining how similar they are to one another and to standard well-being measures. I find important differences in how the models measure households’ resilience capacity, and how they relate to current and future well-being. Due to differences in how they rank households in terms of resilience capacity and how they identify resilient units, their results are not directly comparable. The same households do not get consistently high or low resilience capacity values through all methods, and in two of the three, resilience capacity measures are very dissociated from standard well-being outcomes, both cross-sectionally and in inter-temporal well-being prediction.