Yes, your setup is correct. One could argue that the patients who left the study constitute truncated, not censored, data.
The two steps are also correct. The non-parametric estimate remains constant until another exact life observation is encountered.
You must fit a model to obtain the probability versus time. I recommend a Weibull or a Log Normal distribution model. JMP can do all the models and use a criterion to select the best model, but this data-driven approach is risky when you only have two exact lifetimes.
Here is an example. I used the :weight data column in the Big Class data table and pretended it was lifetime data. I added a Censor column with 1 in all but two rows, so only two exact lifetimes. I launched Life Distribution and selected the Weibull model and scale. You can use the distribution profiler to the right to estimate failure probability for a given time.