need help in logistic regression

Hello everyone,

I tried to understand the relationship between temperature and the
death of an organism by using logistic regression.
glm(formula = Death ~ Temperature, family = binomial(link = "logit"),
data = mydata)

Coefficients:
                           Estimate Std. Error z value Pr(>|z|)
(Intercept)          -87.9161     7.7987  -11.27   <2e-16 ***
Temperature        2.9532     0.2616   11.29   <2e-16 ***

From the above summary, I could understand that log odds of death =

-87.9161 + 2.9532*Temperature.  Odds=exp(log[odds]).  Probability =
odds/(1+odds)

Assuming my data is randomly normal distributed with (u=0, standard
deviation=0.35), and I want to run it for n=10,000, how do I get to
probability from log odds?

Regards,
Eddie