Affective dynamics have been increasingly recognized as important indicators of emotional health and well-being. Depression has been associated with altered affective dynamics, but little is known about how daily life affective dynamics predict depression's naturalistic course. We investigated positive and negative affective dynamics (e.g., inertia, variability, and instability) among adults with depressive disorders (N = 60) and healthy controls (N = 38) in both cross-sectional and prospective analyses predicting weekly depression symptoms over 6 months. Relative to controls, depressed individuals showed elevated daily negative affect (NA) and NA variability along with decreased positive affect (PA). However, groups did not significantly differ on other affective dynamic indices. Based on multivariate prospective analyses of depressed individuals (follow-up N = 36), higher daily NA and lower daily PA were independently associated with higher and average weekly depressive symptom severity over the subsequent 6 months. Exploratory analyses of depression symptom trajectory shape revealed that higher NA and PA variability, NA inertia, and NA instability all predicted an initial increase and eventual return to higher depression symptom levels over the 6-month follow-up period. Daily life affective dynamics may have utility for predicting the naturalistic course of depression, which may help guide interventions targeting affective dynamics in vulnerable individuals.