This study suggests developing a new drought index using the conditional probability of precipitation associated with a wide range of other weather variables, such as temperature, to monitor droughts. Once the marginal probability distributions of the variables become known, it is possible to determine the joint and conditional probabilities through the choice of suitable copula functions. This new drought index of the so-called conditional standardized precipitation index (CSPDI) allows for evaluation of droughts just like the standardized precipitation index (SPI). The L-Moment method was used in the application part of the study to estimate the marginal probabilities of temperature and precipitation; on the other hand, both French-Gumbel Morgenstein (FGM) and Gaussian copula types were used within the case studies to assess joint and conditional probabilities. To evaluate the potential of the proposed drought index, drought patterns were reviewed through this index across several climate zones obtained through the Holdridge Life Zone (HLZ) method. To demonstrate the proposed approach’s capabilities regarding climate change studies, the CSPDI has been applied to the production of the Community Climate System Model (CCSM-4) selected near the major provinces in the country that stand out in population, agriculture, and industrial development. In addition to this, the kriging interpolation technique has been used to embed temperature and precipitation variables recorded by the country’s meteorological stations within the same grid points as the CCSM-4 models. The spatial analysis of the drought patterns using the results of the CCSM4 models and the weather stations established at grid points in the vicinity of the five largest cities of the country provide a useful basis in terms of measuring drought conditions. All these results showed that the CSPDI results changed significantly according to the time characteristics; choosing the temperature as a secondary variable in the CSPDI calculation did not affect the drought model of a rainy weather station such as Rize. But in semi-arid regions such as Izmir and Antalya, both coastal regions, the temperature had a strong effect on drought patterns. Furthermore, the suggested methodology has been applied to the results of GCM models used with CCSM-4 built on the RCP 8.5 scenario. The precipitation and temperatures used in the CSPDI calculations were derived from the NCAR GIS climate model, which allowed the IPCC to apply the CCSM-4 simulation methods in the fifth assessment of the AR5 report.