The frequency, duration, and severity of drought events are expected to increase in the Mediterranean area as a result of climate change, with strong impacts on forest ecosystems and in particular individual tree growth. Tree growth response to drought is strongly influenced by local site and stand characteristics that can be quantified using competition indices (CIs) and water stress indices (WSIs). These indices have been widely used to predict tree growth; however, they are numerous, and few studies have investigated them jointly. In this context, we investigated the potential of using CIs and WSIs to investigate tree behaviour under drought. The main objective of this study was to quantify P. halepensis Mill. annual radial growth using tree size from the previous year, CIs and WSIs. We studied twelve 50-year-old Pinus halepensis plots located in the South-East of France distributed in different density treatments (light, medium and dense). At each plot, all trees were measured (height, circumference), spatialized and the ring-widths were measured for ~15 trees. We also developed a two-strata (over- and understorey) forest water balance model to simulate soil water content at a daily resolution based on stand characteristics (LAI values in particular) and soil properties. A mixed modelling approach was eventually used to investigate the drivers of P. halepensis annual radial growth and to test the performance of five CIs and four WSIs. The best growth model included tree size, the sum of Basal Area of Larger trees in a 5 m-radius (BAL; as CI), and the number of days that trees experienced water stress in a year (as WSI) as predictors. This model explained up to 56% of the variance in observed pine tree growth, which increased up to 77% when the individual tree was included as a random effect on the intercept. We found that distance-independent CIs can perform as well as distance-dependent CIs in our study site. The duration of drought alone appeared to better predict tree growth than drought intensity and duration, or drought timing. The selected model led us to reaffirm the positive effect of thinning on tree secondary growth when facing long and intense drought.