How to deal with missing values when using Random Forrest

I am using the package Random Forrest to test and train a model,
I aim to predict (LengthOfStay.days),:

library(randomForest)
model <- randomForest( LengthOfStay.days~.,data = training,  

+ importance=TRUE,
+ keep.forest=TRUE
+ )
 

*This is a small portion of the data frame:   *

*data(training)*

LengthOfStay.days CharlsonIndex.numeric DSFS.months
1                  0                   0.0         8.5
6                  0                   0.0         3.5
7                  0                   0.0         0.5
8                  0                   0.0         0.5
9                  0                   0.0         1.5
11                 0                   1.5         NaN



*Error message*

Error in na.fail.default(list(LengthOfStay.days = c(0, 0, 0, 0, 0, 0,  : 
  missing values in object,

I would greatly appreciate any help

Thanks

Kevin


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