A system was developed~or olyective prediction oJsurvival which could be applied to all critL"cally ill patients, regardless oJdisease, at an early stage oJhospitaluation. Such a~stem would allow nsk assessment of groupsj?orexperimental studies according to probability oJsurvival and it might allow us to avoid expenditure oJscarce clinical resourceson anima~with little chance of survival. Theprospective study inc!uded200 critically ill dogs: 93Jemales and 107 males, represeno"ng62 breeds. With survival deJned as alive 30 days aj?eradmhsion to ZCL?the overall mortality rate was 40.5% (81 of 200 dogs). Data collected included s@na!ment and parameters that re~ected vital organfinction, the seven"y oJphysiologik derangement and the extent of physiologic reserve. Werecordedthe most abnormal valueJor each parameter within 24 hours oJadmission to ZCUand [o@tik re~ession anafyszk was used to anaZyzeJour d~erent waghting systems. The best model had a concordance0J86.5% with outcome, and it was then re-evaluated to determine whether individual variables cou[d be eliminated without losing predictive accuracy. Four van"ableswere eliminated, resuiti"ng in a~nal mode! with 18 van"ab[es which had 86.3% concordance with outcome. At a 0.5 cut-o~~or predicted risk, the model had sensitivity OJ69%, spea"-Jlci@ @86% and positive predictive value@ 77%. A Receiver Operating Curve was constructed using sen-alcut-o~sJorpredicted outcomefiom 0.1 to 0.9, and the area under the curve was 0.89. Thus, an equaflon was generated thatgives an esa"mateo~the probability o~survival.