Feelings of well-being and happiness fluctuate over time and contexts. Ecological Momentary Assessment (EMA) studies can capture fluctuations in momentary behavior, and experiences by assessing these multiple times per day. Traditionally, EMA was performed using pen and paper. Recently, due to technological advances EMA studies can be conducted more easily with smartphones, a device ubiquitous in our society. The goal of this review was to evaluate the literature on smartphone-based EMA in well-being research in healthy subjects. The systematic review was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. Searching PubMed and Web of Science, we identified 53 studies using smartphone-based EMA of well-being. Studies were heterogeneous in designs, context, and measures. The average study duration was 12.8 days, with well-being assessed 2–12 times per day. Half of the studies included objective data (e.g. location). Only 47.2% reported compliance, indicating a mean of 71.6%. Well-being fluctuated daily and weekly, with higher well-being in evenings and weekends. These fluctuations disappeared when location and activity were accounted for. On average, being in nature and physical activity relates to higher well-being. Working relates to lower well-being, but workplace and company do influence well-being. The important advantages of using smartphones instead of other devices to collect EMAs are the easier data collection and flexible designs. Smartphone-based EMA reach far larger maximum sample sizes and more easily add objective data to their designs than palm-top/PDA studies. Smartphone-based EMA research is feasible to gain insight in well-being fluctuations and its determinants and offers the opportunity for parallel objective data collection. Most studies currently focus on group comparisons, while studies on individual differences in well-being patterns and fluctuations are lacking. We provide recommendations for future smartphone-based EMA research regarding measures, objective data and analyses.