The forecast quality of five seasonal prediction strategies used to obtain tailored bioclimatic indicators in the olive sector has been assessed over the Iberian Peninsula (IP). In total, five indicators have been selected considering their importance in the management of the olive orchard. As time progresses through the indicator target period, the impact of the increasing share of actual observations included in its computation has been evaluated by examining the variabilities of correlation and fair Rank Probability Skill Score (fair RPSS) in each initialization date. The results show that blending either seasonal predictions or climatology with observations enhanced the capability of forecasting the tercile category for all the indicators when compared with the use of climatology or seasonal predictions alone. In fact, for Spring Temperature Maximum (SPRTX) and Growing Season Temperature (GST) indicators, the combination of observations and SEAS5 prediction could outperform the other methods for most of the start months. As for those threshold-defined indicators, namely Spring Heat Days (SPR32) and Summer Heat Stress Days (SU36 and SU40), the end-users are highly encouraged to use climatology in the first month and combine it with observations as soon as they become available.