Objective. To diagnose if a patient has subarachnoid hemorrhage (SAH) and predict if he/she will develop angiographic vasospasm/delayed cerebral ischemia (DCI) or will die using only admission cranial computed tomography (CT) and World Federation of Neurological Surgeons (WFNS) or Hunt-Hess clinical grades. Methods: We developed a semiautomatic method of quantification of SAH volume, surface, sphericity, fractal dimension, and other parameters by retrospectively analyzing admission CT scans of 127 SAH patients. A multivariable model to predict the development of vasospasm/DCI and death was fitted by combining CT and admission neurological grade with derived data. It was also developed and then validated with bootstrapping and with a separate group of patients. Results: The diagnosis of SAH can be given by surface to volume ratio AUC 0.98 (95% CI 0.95-1) , hemorrhage volume 0.92 (95% CI 0.85-0.99), sphericity 0.87 (95% CI 0.73-1) and surface area 0.75 (95% CI 0.56-0.94). For vasospasm/DCI prediction AUC of biomarker panel was 0.731 (95%CI 0.626-0.836) which was significantly different from random (p<0.001) while Hunt-Hess gave 0.653 (95%CI 0.535-0.772). We established one individual image derived predictor of death by the surface to volume ratio of the 60-80 HU volume of interest for blood at the level of AUC (Area under the curve) of 0.777 (95% CI 0.667 - 0.886), while a biomarker panel gave the value of AUC of 0.857 (95%CI 0.769-0.944). These two biomarkers allow the correct prediction of the death of nine of ten patients with 36% and 59% probability, respectively. Conclusions: The model allows rapid, objective, and quantitative assessment of the risk of vasospasm/DCI and death in SAH patients. Both assessments, being fully automatic, can be easily introduced to CT scanner reconstruction software.